This paper considers interdependent electric power and gas supply networks and investigates a dynamic contract mechanism between risk-averse prosumers and a risk-neutral aggregator. The aggregator tries to manage not only financial risks but also power energy and gas energy generated by the prosumers in the presence of uncertain and volatile risk of energy generation processes. The aggregator will determine an incentive condition required of the prosumers so as to indirectly control their actions preferable for the aggregator. We first formulate a novel dynamic contract problem, where each prosumer minimizes an exponential-type cost functional with risk aversion under energy dynamical systems. The problem is regarded as a principal-agent problem in contract theory and the prosumers' optimization problem can be reduced to a Linear Exponential Quadratic Gaussian dynamic game problem. Most part of the solution to the problem considered here can be obtained analytically, while we need to employ a numerical optimization technique to determine the aggregator's action. The effectiveness of the risk-sharing between aggregator and prosumers induced by the proposed mechanism is demonstrated through a simulation.

This paper investigates a smart lane-change mechanism of automated vehicles with intelligent driver model on highways with multiple lanes. In particular, we propose an autonomous lane-change maneuver to improve traffic flow. The key technique of the proposed maneuver is to consider not only selfish conditions to track individual velocity tracking performance but also altruistic conditions to improve the driving performance of the succeeding vehicles by using vehicle-to-vehicle communications. To realize the conditions, this paper presents cost functions and criteria mathematically. We also demonstrate through simulation that the proposed algorithm enhances heterogeneous traffic flow efficiency while avoiding collisions and wasteful traffic congestion in dense traffic. As a result, each vehicle with the proposed maneuver can travel about 1 minute per 10 km faster than only the conventionally selfish condition on average.

© 2018 by the authors. This paper proposes an improved interval fuzzy modeling (imIFML) technique based on modified linear programming and actual boundary points of data. The imIFML technique comprises four design stages. The first stage is based on conventional interval fuzzy modeling (coIFML) with first-order model and linear programming. The second stage defines reference lower and upper bounds of data using MATLAB. The third stage initially adjusts scaling parameters in the modified linear programming. The last stage automatically fine-tunes parameters in the modified linear programming to realize the best possible model. Lower and upper bounds approximated by the imIFML technique are closely fitted to the reference lower and upper bounds, respectively. The proposed imIFML is thus significantly less conservative in cases of large variation in data, while robustness is inherited from the coIFML. Design flowcharts, equations, and sample MATLAB code are presented for reference in future experiments. Performance and efficacy of the introduced imIFML are evaluated to estimate solar photovoltaic, wind and battery power in a demonstrative renewable energy system under large data changes. The effectiveness of the proposed imIFML technique is also compared with the coIFML technique.

This paper proposes a novel load frequency control architecture based on differential games in energy supply-demand network integrating power networks and real-time electricity regulation markets. In order to establish the control architecture that each area minimizes his own cost independently on not only the electricity market layer but also the physical layer, we first present a novel load frequency control in power networks, where set-point signals from electricity markets depend on competitive bidding among utilities in each area and they are regarded as stationary disturbances in power networks. Then, we show that the control problem can be reduced to a finite-horizon differential game and the solution of the differential game control problem is analytically given by a feedback Nash equilibrium. The effectiveness of the proposed control mechanism is finally demonstrated through simulations with two-area power and electricity market network model.

© 2016 Elsevier Ltd This study proposes a two-level coordinated control strategy with fuzzy logic for appropriately adjusting the total active power supplied to a grid by large-scale photovoltaic (PV) farms in order to regulate grid frequency. For a solar farm, the strategy includes a central coordinating controller and many local controllers at PV power assemblies, treated as agents. In detail, the central controller uses a frequency regulation module based on a new automatic-tuning fuzzy-logic controller scheme to compute the appropriate reference values according to the total power needed. Then, the individual reference value for each local controller is determined. Each local controller governs all power-electronic converters installed at the PV agent to inject power into the grid according to the individual reference value received. Additionally, each local controller uses an algorithm to manage the state-of-charge of the battery bank installed at the agent so that it remains in the safe range of 20–80% while operating and close to the desired idle value of 50% at the steady state. Besides, a special control mode is developed and integrated into the overall strategy to aid rapid recovery of the grid frequency under emergency conditions. Numerical simulations demonstrate that the suggested strategy has the good response in terms of injecting an appropriate amount of power into the grid to regulate the frequency deviation into acceptable ranges of ±0.2 (Hz) in the transient state and ±0.05 (Hz) at the steady state, even when the weather conditions (solar radiation, air temperature), AC system load, and important control parameters of the grid suddenly change. Furthermore, the effectiveness in improving the grid-frequency stabilization by using the proposed strategy is validated within a four-area power system, where four PV farms are connected and the operating parameters of the grids at the areas are fairly different.

© 2016 The Society of Instrument and Control Engineers - SICE. This paper presents a newly modified control scheme using artificial neural network (ANN) for doubly fed induction generator (DFIG) connected with a wind turbine under the unbalance of three-phase grid voltages. In detail, the proposed scheme is based on the stator flux oriented control (SFOC), and it consists of a Sequence Component controller (SCC) and a unique PI with ANN (PI-ANN) hybrid controller. The main objectives of the suggested scheme are to regulate independently the output active and reactive powers of DFIG and to diminish significantly harmonics in the rotor current during the unbalanced grid voltage dips. Numerical simulations, including considerations on sudden changes of reference values for the powers and the random alteration of wind speed, are performed in MATLAB to evaluate effectiveness of the proposed scheme. Furthermore, detailed comparisons between simulation results under the unbalanced voltage dips, obtained with the traditional PI method, PI with fuzzy logic (PI-F) hybrid technique and suggested PI-ANN scheme, also are illustrated to validate the salient performance of the presented control structure.

© 2016, European Association for the Development of Renewable Energy, Environment and Power Quality (EA4EPQ). All rights reserved. This paper presents a pretty comprehensive analysis on stability issues of control for active power filter (APF) installed in an electric grid where megawatt doubly fed induction generator (DFIG) wind farm is connected. Major objectives of this paper are to evaluate roles and impacts of main design parameters in the controller of APF. As well, the ultimate goal is to determine the stable value range and the suitable-performance value range for a proportional control coefficient in APF. Wherein, firstly, background theories of the voltage-detection control method for APF to reduce the voltage and current distortions on the electric grid are described. Furthermore, an appropriate equivalent circuit of a typical grid-connected DFIG wind farm with APF to analyze impedance in the frequency domain is introduced. After that, mathematical formulas and algorithm to determine the stable value range and suitable performance value range for the control coefficient in APF are proposed. Finally, results obtained with the suggested equivalent circuit and impedance analysis technique are shown and discussed in detail. Besides, different operation cases of the controller of APF and the illustrative DFIG wind farm, including parametric uncertainties of the electric grid, also are examined to assess effectiveness of the proposed analysis algorithm.

© 2015 IEEE. This paper presents a novel control strategy based on fuzzy logic to adjust fittingly the total output-active power injected into a local grid from a large-scale photovoltaic (PV) farm to support grid-frequency regulation. The strategy consists of a central coordinating controller and local controllers at PV power agents. Wherein, the central controller uses a frequency regulation module based on a unique fuzzy logic controller (FLC) to determine the reference value of total active power needed; and then appropriately coordinates the individual reference value for the local controller at each PV agent. As well, each local controller drives all the power-electronic converters and battery charger installed at PV agent to deliver power to the grid exactly according to the reference value obtained from the central controller. Besides, in each local controller, a simulation module based on the mathematical model of PV panel is used to predict beforehand the maximum power from PV arrays, and a control algorithm to regulate state-of-charge (SOC) of the battery bank is also implemented. Simulation results show that the proposed strategy has good performance in delivering the active power to grid with regulating the grid frequency in tolerable ranges even if the AC-system load and solar irradiation unexpectedly vary. Moreover, efficacy in regulating grid frequency of the suggested strategy is also compared with the conventional strategy which uses the full maximum power point tracking (MPPT) mode.

© 2014 Chinese Automatic Control Society and Wiley Publishing Asia Pty Ltd. This paper discusses two techniques based on the feedback linearization (FBL) method to control the active and reactive output powers of three-phase grid-connected photovoltaic (PV) inverters. The first control scheme is an application of the direct FBL approach. The other is an appropriate combination of the FBL and fuzzy logic (FBL-FL), and is the main proposed method of this study. Wherein, a unique fuzzy logic controller (FLC) is designed to enhance effectiveness of the linear control method used in the direct FBL. In detail, its major objectives are to improve the transient response and reduce steady-state oscillations in the output powers. In this research, the illustrative PV inverter utilizes a three-level DC-AC converter, an R-L filter and a 250V/10kV wye-wye transformer to inject the energy, obtained from PV array with a nominal power of 100kW, into the 10kV/60Hz three-phase grid. Numerical simulations in MATLAB and PSIM illustrate that the two FBL-based structures perform very well in independently regulating the active and reactive output powers to the reference values, even within the parametric uncertainties and the unbalanced grid voltage condition. Moreover, comparisons of simulation results, obtained from the traditional proportional-integral (PI) control and the two FBL-based structures, show advantages of the proposed FBL-FL hybrid technique in terms of fast response, small overshoot, acceptable steady-state fluctuation and high robustness.

© 2014 SICE. This paper presents modified Stator Voltage Oriented Control (SVOC) for Doubly Fed Induction Generator (DFIG) in wind turbines to reduce torque pulsation during unbalanced voltage dips, and current waveforms are also improved with the decreasing of harmonics. The proposed schemes utilize multiple PI controllers with anti-windup to obtain commanded rotor currents and also introduce extra commanded values for rotor current; as well, Notch filters are used to eliminate the second-order harmonic components. The designed system consists of a wound-rotor induction generator and back-to-back power-electronic converters connected to both rotor and grid sides. Wherein, the modifications are applied to the control of rotor side converter (RSC). Simulations in Matlab/Simulink illustrate the enhanced stability of torque response and the improvement of current waveform. Comparisons of the simulation results with a traditional Stator Flux Oriented Control (SFOC) and a previously suggested modification of SFOC for operation under unbalanced voltage dip are provided to evaluate the newly proposed methods in the paper.

© 2014 IEEE. This paper presents a comprehensive analysis technique about harmonic resonance issues in megawatt grid-connected wind farms where the doubly fed induction generator (DFIG) is used. Wherein, firstly, the background theories of the series resonance, parallel resonance and their impacts on the electric system are described. Moreover, a suitable equivalent circuit of typical grid-connected DFIG wind farms for analyzing impedance in the frequency domain is proposed. Then, mathematical formulas are introduced detail to determine exactly orders and amplifications of the voltage and current distortions on both the medium-voltage (MV) bus and low-voltage (LV) bus. Lastly, results obtained from the proposed equivalent circuit and impedance analysis technique are compared to other results achieved with the detailed wind farm simulated in MATLAB/SimPowerSystems. As well, many different operation cases of the illustrative grid-connected DFIG wind farm, including parametric variations, are also examined to evaluate the accuracy and effectiveness of the proposed analysis technique.

Lysosomes contain various hydrolases that can degrade proteins, lipids, nucleic acids and carbohydrates. We recently discovered "RNautophagy," an autophagic pathway in which RNA is directly taken up by lysosomes and degraded. A lysosomal membrane protein, LAMP2C, a splice variant of LAMP2, binds to RNA and acts as a receptor for this pathway. In the present study, we show that DNA is also directly taken up by lysosomes and degraded. Like RNautophagy, this autophagic pathway, which we term "DNautophagy," is dependent on ATP. The cytosolic sequence of LAMP2C also directly interacts with DNA, and LAMP2C functions as a receptor for DNautophagy, in addition to RNautophagy. Similarly to RNA, DNA binds to the cytosolic sequences of fly and nematode LAMP orthologs. Together with the findings of our previous study, our present findings suggest that RNautophagy and DNautophagy are evolutionarily conserved systems in Metazoa.

This paper presents two techniques based on the feedback linearization (FBL) method to control the active and reactive output powers of three-phase grid-connected photovoltaic (PV) inverters. Wherein, the first suggested control scheme is an adoption of the direct FBL approach. The other is an appropriate combination of the FBL and fuzzy logic (FBL-FL), and it is also the main proposed method of this research. In detail, a unique fuzzy logic controller (FLC) is designed to enhance the effectiveness of the suggested FBL, especially in reducing fluctuations in the active and reactive output powers at the steady state. In this study, the demonstrative PV inverter uses a three-level DC-AC converter, an L-type filter and a 250V/10kV wye-wye transformer to inject the energy, obtained from PV array with a nominal power of 100kW, into the 10kV/60Hz three-phase grid. Simulations illustrate that two suggested control schemes have good performances in regulating independently active and reactive output powers to the references, even within parametric uncertainties. Furthermore, comparisons of simulation results, obtained from the traditional PI control and two the presented FBL-based structures, show salient advantages of the proposed FBL-FL technique in terms of quick response, slight overshoot, small steady-state oscillation and high robustness. © 2013 Engineers Australia.

Regulated degradation of cellular components by lysosomes is essential to maintain biological homeostasis. In mammals, three forms of autophagy, macroautophagy, microautophagy and chaperone-mediated autophagy (CMA), have been identified. Here, we showed a novel type of autophagy, in which RNA is taken up directly into lysosomes for degradation. This pathway, which we term 'RNautophagy,' is ATP-dependent, and unlike CMA, is independent of HSPA8/ Hsc70. LAMP2C, a lysosomal membrane protein, serves as a receptor for this pathway. The cytosolic tail of LAMP2C specifically binds to almost all total RNA derived from mouse brain. The cytosolic sequence of LAMP2C and its affinity for RNA are evolutionarily conserved from nematodes to humans. Our findings shed light on the mechanisms underlying RNA homeostasis in higher eukaryotes. © 2013 Landes Bioscience.

The KaiC phosphorylation cycle generates the circadian rhythm without the transcription and translation of kai genes. To study the mechanism of the circadian rhythm, we use the model proposed by Kurosawa et al, describing the KaiC phosphorylation process in DD case. The temperature compensation is one of the most important features of the circadian rhythm. Therefore, some methods used to construct the temperature compensated model, have been proposed. In this paper, we applied the gain scheduling method proposed by Takeuchi to the model. In which, we focused on another essential feature named "temperature entrainment". This study investigates the mechanism of the phase shift and the temperature entrainment by using the temperature compensated model under the temperature cycle. Simulations results, including the comparison with the biological experiments, clearly illustrate the effectiveness of the proposed model.

This paper presents a comprehensive method to design a compatible controller system for the photovoltaic (PV) single-phase grid-connected system. The demonstrative PV system in this study consists of four 250W solar panels with a nominal total power of 1 kW, a non-inverting buck-boost DC-DC converter, and a DC-AC inverter, including a LCL output filter. Main objectives of the PV system in use are threefold: tracking and operating at the maximum power point (MPP) of the PV array, regulating the DC link voltage to 200 V, and delivering the power to the 110V/60Hz electric grid with unity power factor (PF). To fulfill three above goals respectively, the designed controller system is composed of three major modules. In which the first is the MPPT Controller module, using an improved incremental conductance (INC) algorithm based on fuzzy logic. Another is the DC Link Voltage Regulator module constituted by a PI-Fuzzy hybrid controller. And the last is the Current Controller module based on the backstepping approach. Simulations show that the proposed controller system completely accomplishes listed aims even when the solar radiation and temperature change suddenly.

Output smoothing using storage facilities for wind turbine generators has been realized typically by means of a first order system, as a low pass filter, together with compensators for keeping a level of energy storage and several limiters for energy flows; however, it is not easy to achieve an appropriate combination of the filter, the compensators and the limiters, for a desired performance of the output smoothing. To overcome this difficulty, we propose a new scheme of the output smoothing, which generates, by solving a Model Predictive Control (MPC) problem, an optimal reference signal for storage facilities so that the output smoothing is achieved and the constraints on the storage level and the energy flows are satisfied; in this scheme, trade-offs among smoothing performance and constraint fulfillment levels can be designed by selecting weighting parameters in the performance index. We perform numerical simulations, and discuss usability of the proposed scheme by comparing it with the existing output smoothing methods using fixed time-constant filter.

Interval consensus problem of multi-agent systems is a new consensus problem in which the multi-agent system given by the proposed protocol can globally asymptotically converge to a specified point on the closed and bounded interval. In this paper, we discuss interval consensus problem of multi-agent systems with two types of time-delays, i.e., communication delay and input delay. Our work shows that the communication delay does not affect the consensus while the input delay does. For communication delay, the system given by the proposed protocol can reach globally asymptotically interval consensus with any time delay. As for bounded input delay, the system given by the proposed protocol can reach globally asymptotically interval consensus and then the system can also achieve a generalized interval average-consensus if the directed graph is balanced. Simulations are provided that demonstrate the effectiveness of our theoretical results.

This paper presents both the previously and newly modified Stator Flux Oriented Control (SFOC) and Direct Power Control (DPC) structures for Doubly Fed Induction Generator (DFIG) in wind turbines to improve responses of active power, reactive power and generator's torque during the grid voltage unbalance. In the newly proposed SFOC-based scheme, which emphasizes on improvement of generator's torque performance, PI controllers with anti-windup, Notch filters and the Sequence Component Controller (SCC) are utilized. The other control techniques use single or multiple applications of PI controller with anti-windup, hybrid PI-Fuzzy controller with anti-windup and Notch filter to eliminate the second-order harmonic components. The designed system consists of a wound rotor induction generator and power-electronics converters at both rotor and grid sides. The modifications are applied to the rotor side converter (RSC). Simulations in Matlab/Simulink illustrate the enhanced stability of torque, active and reactive powers delivered by DFIG in both the SFOC-based and DPC-based schemes. Moreover, comparisons in simulation results, obtained separately from all the presented control structures, are provided to evaluate the effectiveness of the newly proposed scheme.

Cluster consensus problem of the multi-agent systems with communication delay is studied in this paper. We consider the multi-agent systems with a special Laplacian matrix as its system matrix. For two types of protocols wIth time-delay, our work shows that the multi-agent systems with communi ation delays can reach cluster consensus. Some numerical simulations are given to verify the effectiveness of the theoretlcal results.

We consider a dynamic game model of power networks with generators and/or consumers, called agents, and one public commission, called utility
a game with a prescribed dynamic mechanism is performed such that each agent decides a private control to minimize its own cost functional, and the utility manages information transmissions between the utility and agents and decides command signals, called prices, to minimize a public cost functional. We discuss designs of the mechanism that integrates strategic determinations of private controls by the agents into the optimal public controls that achieve the optimal social welfare and rational agents can accept. The model of this paper is a generic linear Gaussian model of power networks, which is motivated by so-called average system frequency models
in each model of the agents, we includes the type parameter presenting each agent's private information
we also consider the time delay in calculation of prices by utility. Assuming that each private cost functional as well as the public cost functional is quadratic, we derive formulas of the pricing schemes, and the incentive cost, inspired by the pivot function in the mechanism design theory literate from economics, that characterize our mechanism design in both formulations of the fixed horizon control and the receding horizon control cases. © 2013 IEEE.

Consensus problem of multi-agent systems with communication channel constraint is studied by providing a special Laplacian of directed graphs in this paper. Communication delays as one kind of channel constrains in multi-agent systems have been discussed in the recent literature. Different from those works, consensus problem with communication channel constraint on signal amplitude is addressed in this paper. Our work shows that the consensus can be obtained as long as some state-dependent switching parameters are introduced into the consensus protocol. It is shown that the system given by the proposed protocol can reach globally asymptotically consensus and that the system can also achieve a generalized average-consensus if the directed graph is balanced. An example has been proposed to illustrate the effectiveness of the method.

This paper investigates the consensus problem of the second-order multi-agent systems with communication channel constraint on signal amplitude. Communication delays as one kind of channel constraints in the second-order multi-agent systems have been discussed in the recent literature while in this paper consensus problem of second-order multi-agent systems with communication channel constraint on signal amplitude is investigated. A state-dependent switching parameter is introduced into the consensus protocol. A sufficient condition is obtained for the consensus problem of the second-order multi-agent systems with communication channel constraint based on our early work. A simple example is also given to verify the effectiveness of the proposed theorem.

Consensus problem of multi-agent systems with sensing constraint on range is studied in this paper. It is known that sensors have limited sensing capabilities although they are very important components and play a vital role in networked control systems. This paper discusses the consensus problem of the multi-agent systems in which some agents are outside the sensing ranges of their neighbors. We introduce an initial-state-dependent switching parameter into the consensus protocol, and show that the consensus can be obtained as long as some conditions are satisfied. An example is proposed to illustrate the effectiveness of the method.

Cluster consensus problem of the multi-agent systems with signal amplitude constraint in communication is studied by providing a special Laplacian of directed graphs in this paper. A sufficient condition is obtained for the cluster consensus problem of the multi-agent systems with signal amplitude constraint in communication by introducing a state-dependent switching parameter into the cluster consensus protocol. A numerical simulation is given to verify the effectiveness of the theoretical analysis.

The presence of state and control constraints in physi cal systems may lead to performance deterioration and instability if not adequately accounted for in controller design processes. Therefore, a procedure of state and control constraint fulfillment for uncertain linear systems, which firstly require an adaptive controller, is proposed. Model Reference Adaptive Control (MRAC) Method is selected to design the controller, and Lyapunov stability theory is used to obtained adaptive laws. To solve the constraint fulfillment problem, a concept of maximal output admissible set [8], [11] is utilized to predict safe operation of the plant. Constraint fulfill ment procedure is described as polynomial optimization problems, and a numerical design example is carried out to support the arguments.

Modeling the driver behavior is expected to play a fundamental role in designing systems of driver monitoring, warning, assist control and training. In this paper, we present an identification method of automobile driver operations based on a hierarchical clustering approach, which leads to a stochastic piecewise affine (PWA) model. The driver behavior can be viewed as an outcome of the hybrid system that consists of (continuous) primitive driving operations and their (discrete) switchings. We describe the driving primitives by PWA models and the switchings by hidden Markov models (HMMs). One significant issue of this hybrid modeling is to extract the distinct states of driving operation from the driver behavior and determine the number of the states. To this problem, we propose a method to estimate the number of states using an idea of hierarchical clustering. We apply our identification method to the accelerator operations of driver, and demonstrate its efficacy through numerical experiments using the real data of four drivers.

The linear noise approximation is a useful method for stochastic noise evaluations in genetic regulatory networks, where the covariance equation described as a Lyapunov equation plays a central role. We discuss the linear noise approximation method for evaluations of an intrinsic noise in autonomously oscillatory genetic networks; in such oscillatory networks, the covariance equation becomes a periodic differential equation that provides generally an unbounded covariance matrix, so that the standard method of noise evaluation based on the covariance matrix cannot be adopted directly. In this paper, we develop a new method of noise evaluation in oscillatory genetic networks; first, we investigate structural properties, e.g., orbital stability and periodicity, of the solutions to the covariance equation given as a periodic Lyapunov differential equation by using the Floquet-Lyapunov theory, and propose a global measure for evaluating stochastic amplitude fluctuations on the periodic trajectory; we also derive an evaluation formula for the period fluctuation. Finally, we apply our method to a model of circadian oscillations based on negative auto-regulation of gene expression, and show validity of our method by comparing the evaluation results with stochastic simulations. (C) 2010 Elsevier Ltd. All rights reserved.

Ubiquitin-C-terminal hydrolase L1 (UCH-L1) is a de-ubiquitinating enzyme expressed in the brain and reproductive tissues as well as certain cancers. The hydrolase activity of UCH-L1 has been implicated in Alzheimer's disease and cancer invasion; therefore, it may represent a therapeutic target for these diseases. The present study was undertaken to identify novel chemical modulators for the hydrolase activity of UCH-L1. To identify chemicals that bind to the active site of UCH-L1, we carried out in silico structure-based drug screening using human UCH-L1 crystal structure data (PDB ID: 2ETL) and virtual compound libraries containing 26,891 and 304,205 compounds. Among the compounds with the highest binding scores, we identified one that potentiates the hydrolase activity of UCH-L1, and six that inhibit the activity in enzymatic assays. These compounds may be useful for research on UCH-L1 function, and could lead to candidate therapeutics for UCH-L1-associated diseases. (C) 2010 Elsevier Ltd. All rights reserved.

The large scale database-based online modeling called LOM is the one of local modeling method. This method has been developed to apply the just-in-time modeling for the blast furnace by us. In this paper, we propose two new types of local models in LOM to improve the prediction performance. One is used weighted multiple regression model as a linear local model of LOM. The other is used on-line Bayesian learning model as a nonlinear local model of LOM. In order to compare the prediction performance of the two types of local models in LOM, we evaluate the prediction performance by using the real process data of the blast furnace.

In this paper, a new automobile gear-shift control for Continuously Variable Transmissions (CVTs) is presented. Conventional gear-shift control is based on so-called maps. Its setting is generally conservative and drivers can change shift maps themselves by operating switches such as a gear-shift or tip switches. However, it is troublesome for the drivers who are not positive for driving to operate them. To overcome this problem, we design a new gear-shift control for CVTs considering the driver characteristics of gear-shift operation based on a Just-In-Time(JIT) modeling. In addition, we reduce the number of input variables of the JIT model by linear regression in view of the limits on memory capacity and computational load for on-line calculation. Furthermore, the output of JIT model is smoothed with the least squares B-spline interpolation. Our experiments show that it has downshifted automatically on demand without driver's gear-shift operation when approaching curves.

Using the linear noise approximation, we approch to the problem of evaluation and prediction of behavior of autonomous oscillatory genetic networks fluctuated by intrinsic noise. In this approach, the state covariance of the networks represents all the information concerning the fluctuation by intrinsic noise, and further, when the genetic network is an autonomous oscillatory system, the state covariance obeys a periodic Lyapunov differential equation that has generally unbounded solutions. Based on the analysis of stability and periodicity properties of the solution to the periodic Lyapunov differential equation, we propose two measures for evaluating intrinsic noise. Circadian clock is a typical example of autonoumous oscillatory genetic networks. Focusing on the simple core model (Gonze and Goldbeter, 2006) for circadian clocks and using the proposed measures, we evaluate robust performances concerning periodicity and amplitude of oscillations in the model fluctuated by intrinsic noise by changing system parameters.

The Lyapunov equation, which describes stochastic variations of systems as a covariance equation, plays a central role in evaluation and prediction of behavior of genetic regulatory networks fluctuated by molecular noises. When the genetic network is an autonomously oscillatory system, the Lyapunov equation becomes a periodic differential equation that has generally unbounded solutions. We discuss orbital stability and periodicity properties of the solutions to the periodic Lyapunov differential equation by using Floquet-Lyapunov theory, and propose two global measures for evaluating stochastic fluctuations of the whole periodic trajectory. We also provide an evaluation formula for the period fluctuation.

In this paper, we develop a method to realize an autonomous periodic motion of a small blimp system in a horizontal plane. The idea behind the method is to make the dynamics of a small blimp system approach asymptotically to that of the van der Pol equation that has a limit cycle. The method consists of the following two steps: First, we introduce two constraints. One has a role to connect the motion equation of a small blimp system with the van der Pol equation, and the other has a role to divide the coupled system into two independent systems. Second, we design an output stabilizing controller for each of two independent systems, so that the two constraints are fulfilled.

The large scale database-based online modeling, called LOM, is a type of Just-In-Time modeling for blast furnace. In this paper, we propose a new type of LOM using a nonlinear local model to improve the performance of the long-term prediction. To estimate the parameter of the nonlinear local model, we use on-line Bayesian learning scheme with Sequential Monte Carlo. The prediction performance of the new LOM is demonstrated by using the real process data of blast furnace.

The sensor scheduling is to select a sensor (or a group of sensors) from multiple sensors at each time step so as to perform optimally a task based on the sensed data. In this paper, we pose a model predictive type deterministic/stochastic sensor scheduling problem for discrete-time linear Gaussian time-varying systems, and develop an approach to solve these problems based on the dynamic programming recursion. We show first that, in a special case of deterministic scheduling where the Riccati recursion of error covariance satisfies a specific structural condition, the online optimization using the dynamic programming is reduced to a static optimization, so that the model predictive sensor scheduling can be easily implemented online. Next, we discuss the stochastic scheduling problem, and show an alternative condition of optimization reduction, which lead to a stochastic sensor scheduling easily implemented online. Finally, we propose two practical sensor schedulings for deterministic and stochastic case, and discuss an example to illustrate the two sensor schedulings.

We propose a design method of disturbance attenuation type distributed control for identical decoupled linear systems together with conditions for stability of the closed loop global system. Using a simple example of formation flight corrupted by disturbances, we compare the design by the proposed method with that by the LQ control method in Borrelli and Keviczky (2006); we consider two kinds of disturbances, system disturbances and parameter variation. And we demonstrate that proposed method has superior robustness against disturbances.

From the viewpoint that reaction rates will change with temperature, we present a general method to build circadian clock models that generate circadian oscillations with almost constant period under different constant ambient temperature, and propose an algorithm estimating the parameter condition for compensated period against the change of temperature based on the PER single-feedback loop model of Goldbeter [1995. A model for circadian oscillations in the Drosophila period protein (PER). Proc. R. Soc. London Ser. B 261, 319-324] for Drosophila. We show that the model with derived parameters can realize the temperature compensation over a wide range of temperature, and simultaneously can realize the entrainment to temperature cycles. (c) 2007 Elsevier Ltd. All rights reserved.

This paper reports a sequential prediction system of "Large scale database-based Online Modeling (LOM)". The sequential prediction system predicts time-series process variables repeating processing that predicts process variables of next step by using the predicted process variables of previous step and prepared manipulated variables. Furthermore, the system is applied to the industrial reactor; Practical effectiveness of the system is verified. As the result, the system has predicted the process variables with satisfactory accuracy. The practical effectiveness has been confirmed. ©ICROS.

In this paper we focus on control of affine systems with discrete inputs, which is a class of hybrid systems. An example of those systems is a DC- DC converter controlled by transistor switches. We propose a design method of switching conditions, which transfers state of systems to a neighborhood of a specified state and keeps it there, using sliding mode with hysteresis layer. Finally effectiveness of this method is shown by simulation and experimental result.

The interactions among the components of biological systems, which are DNA, RNA and proteins, create specific cell functions. Recently, many works try to understand mechanism of the interactions from dynamical systems viewpoints, and for this problem, concepts and results in control engineering are expected to play significant role. However, the biological systems are generally nonlinear and complex, and are difficult objects of analysis and synthesis. In this paper, we propose an evaluation method, which is based on orbital stability analysis, of identifying important parts of nonlinear systems that have periodic orbits such as circadian rhythms or cell cycle control, and apply the method to a circadian rhythm model for Drosophila proposed by Leloup and Goldbeter (1998). © 2007 SICE.

This paper discusses the H-infinity control synthesis for discrete-time linear networked systems with time-varying delays in input and output channels. The time-varying delays are assumed to take their values in finite sets, and assumed to be measurable only on line. Our formulation allows the (worst) case of random delays with no stochastic assumption. Considering delays as parameters, we first reformulate the H-infinity control problem for networked systems with time-varying delays into that for linear parameter-varying (LPV) systems with jumping parameters. Next, we present a sufficient condition, which is given as a finite set of linear matrix inequalities (LMIs) depending on values of parameters, for synthesizing a gain scheduled output feedback control for LPV systems with jumping parameters, and based on this condition, derive an output feedback controller scheduled with input-output delays. Finally, applying our controller to the networked system composed of the cart and inverted pendulum plant and the input-output channels with random jumping delays, we show that our controller, which does not assume any stochastic property on delays, displays a good performance almost similar to that of the existing stochastic H-infinity controller.

We develop an approach to robustness analysis of circadian rhythms from the viewpoints of (local) robust stability of periodic trajectories and their period-sensitivity, based on mathematical models. Our attention is directed to the core molecular model generating circadian rhythms in Drosophila, proposed by Goldbeter [1], for our approach to be illustrated. We consider two cases when the circadian rhythms are subjected to periodic forcing by light/dark (LD) cycles and when the circadian rhythms are under continuous darkness (DID). First, we propose conditions/algorithms for (local) robust stability, and show that the circadian rhythms generated by the core molecular model are (locally) robustly stable, in both LD and DD cases. Second, in DD case, we derive a formula of period sensitivity, and assess effects of (infinitesimal) parameter-variations on the period of the circadian rhythms.

In the field of pig ironmaking process, operation malfunction is caused by both enlarging a blast furnace and increasing use of low quality ore. Thus, operation support systems predicting a blast furnace performance are demanded. This paper reports a Java-based operation support system integrated with a "Large-scale database-based Online Modeling (LOM)" and a blast furnace simulator. The system predicts blast furnace performance by combining the partial unsteady simulator of the physical modeling method and the LOM of the local modeling method and supports the operation. To construct the system, the Java-based partial unsteady simulator is developed and the existing LOM is rebuilt by using versatile database and Java to realize the generalized LOM with general versatility. These systems are integrated by using Java.

Circadian rhythms, which are observed in most of living things, e.g. bacteria, fungi, plants, and animals, are self-sustained oscillations with about 24 hours period, and have the following properties: The first property is that the oscillation is entrained by light/dark cycles; the second one is that the oscillation, especially the period of the oscillation, is robust against changes of environment. In this paper, we investigate these two properties from control theoretic viewpoints. First, considering light/dark cycle as periodic control input, we try to explain how periodic control inputs can entrain one self-sustained circadian oscillator described by a core molecular model for Drosophila by Goldbeter (1995). Second, for structural understanding of robustness of circadian rhythms, we propose an evaluation method of the robustness based on period sensitivity, and try to design some rate parameters, which are regarded as control parameters, based on some optimizations using a robustness measure, when a rate parameter is moved to outside of normal area by environmental changes.

Visual Servoing (VS) has so many advantages and potentialities in applications that it has been studied intensively from several viewpoints. To realize VS, we have to deal with constraints necessary for VS such as keeping all features of moving target in the field of view and avoiding saturation of manipulator torque limitation. In this paper, we propose a new method to construct VS system taking the constraints for VS into account explicitly based on reachable sets for systems with bounded disturbance. We propose also a switching strategy to get the controller more high performance in addition to constraint fulfillment. We demonstrate efficacies of this method by performing a experiment of VS using 6link manipulator PA10.

In this paper, development of LOM with general versatility (Generalized LOM) and its speed enhancement technology are described. An existing LOM is rebuilt by using versatile database and Java to realize the "Generalized LOM". The Generalized LOM doesn't depend on the software platform and it is convenient to use the network and the visualization. Furthermore, the speed of the Generalized LOM is enhanced. The processing time is shortened without reducing the prediction accuracy.

In the field of pig ironmaking process, operation malfunction is caused by both enlarging a blast furnace and increasing use of low quality ore. Thus, operation support systems predicting a blast furnace performance are demanded. This paper reports application of a partial unsteady simulator and a "Large-scale database-based Online Modeling (LOM)"for blast furnace operation support. First, the partial unsteady simulator constructed by using steady model as fundamental model is described. Second, a generalized LOM rebuilt by the existing LOM system is introduced. Third, a Java-based operation support system is described. The system is realized by combining the simulator of the physical modeling method and the LOM of the local modeling method. The system predicts dynamic molten pig-iron temperature in blast furnace. To predict the dynamic molten pig-iron temperature, a basic tank model of metal and slag is incorporated into. the simulator. Functions representing effect of pulverized coal injection are incorporated into the unsteady model.

The large scale databace-based online modeling, called LOM, is a type of Just-In-Time modeling for blast furnace. The database of LOM is so far built by quantizing directly measurement process data. Recently it has been shown that the image data generated by visualizing shaft pressure and stave temperature is very useful for blast furnace operation and guidance. In this paper we try to extend LOM to the one incorporated with the visualized process data. First we extract features of the visualized process data by using independent component analysis (ICA), and add the features (independent components) of the visualized process data, as process data, to the database of LOM. Prediction performance of the extended LOM is illustrated by using real process data.

A practical method of JIT modelling for a blast furnace process data whose characteristics are very complicated physical phenomena and stiff nonlinear process are studied. The proposed method is composed of severely selecting process data variables by stepwise method and searching the past similar data in quantized topological space constructed by the selected variables. The effectiveness of this method is confirmed. It is also confirmed that it is sufficiently possible to apply this method to online use because the calculation time is quite short for searching the past similar data and estimating the future. Copyright © 2005 IFAC.

In this paper, we design Active Queue Management scheme for dynamical models of compuer network based on control theory. TCP/AQM (Transmission Control Protocol/Active Queue Management) network models are nonlinear and including time-delay. Taking these characteristics into account explicitly, we popose a new design method of AQM controller. Especially, paying attention that time-delay is depend on queue length clearly, we suggest an appropriate gain-scheduling controller based on new type of Linear Parameter Varying (LPV) systems with parameterdependent time-delay. Effectiveness of the proposed method is evaluated by using matlab and ns-2(Network Simulator Ver. 2).

We discuss a finite horizon H-infinity control problem for time-varying systems with input delays. Clarifying a relationship between two H-infinity control problems in input delay case and in measurement delay case, we derive a solution in input delay case based on the known result for the H-infinity control problem in measurement delay case, and show that the solution has the same predictor-observer structure as the solution in measurement delay case has. Using this structural information on the solution, we also present an elementary proof of the solution to the finite horizon H-infinity control problem for systems with input delays, which is based only on completion of squares. (C) 2004 Elsevier Ltd. All rights reserved.

The load variation of the electrohydraulic servo system causes degradation of the control characteristic. This is because the flow characteristic of the flow control valve depends on the load condition. Here, we propose the flow calculation formula to have continuous flow between turbulent and laminar flow so that we compose the linear plant model with a scheduling parameter. Then, we design gain-scheduled controllers for the velocity and hydraulic force control. (C) 2003 Wiley Periodicals, Inc. Electr Eng Jpn, 146(3): 65-73, 2004; Published online in Wiley InterScience (www.interscience.wiley.com). DOI 10.1002/ eej.10239.

In this paper, we approach to robustness of circadian rhythms from the viewpoint of (local) robust stability of periodic trajectories. We use the core molecular model proposed by Goldbeter (1995) for cases when the circadian rhythms are not only subjected to periodic forcing by light/dark (LD) cycles but also under continuous darkness. We propose conditions/algorithms to test the robustness for both cases.

With the advance of computer hardware performance and database system technology, it has been practicable to store and to search for a large quantity of data. So that Local modeling method, such as Just-In-Time modeling, has become very attractive in recent years. We have developed "Large scale database-based Online Modeling" as the practical method based on the Just-In-Time modeling concept on blast furnace operation, which has very complicated physical phenomena and strong non-linear specific characteristics. The validity of the developed modeling method has been confirmed by the study with blast furnace operation data, then the past similar operation data have been searched and the prospective operation data have been estimated very quickly and precisely.

We formulate H-infinity control problems for linear systems with delays in input and output, and discuss possibility of finite-dimensional characterizations of solutions. In the case when delay exists in control input and controlled output, first, we derive an output feedback H-infinity control formula of the central solution type, Which is given by using solutions of finite- and infinite-dimensional Riccati matrix inequalities. Second, we show that, if the controlled output is chosen such that it satisfies the 'prediction condition', the solution to the infinite-dimensional Riccati inequality can be calculated by solving a finite-dimensional Riccati inequality. We provide a system theoretic interpretation for the prediction condition, and show that, if the prediction condition is satisfied, there is an equivalent H-infinity control problem for finite-dimensional linear systems with no delay. Finally, the equivalence result is extended to the case when delay exists also in measurement output. Copyright (C) 2003 John Wiley Sons, Ltd.

This paper considers output feedback control problems for bilinear systems with a quadratic cost function and develops a robust control theory approach. A key point of the approach is to regard once the bilinear term as a term with unknown parameters and then use some robust control synthesis methods. This approach derives two types of nonlinear output feedback controller that guarantee an upper bound for the cost function. Efficiencies of the proposed approach are also demonstrated through a numerical example.

This paper considers synthesis problems of output feedback controllers for linear time-delay systems via infinite-dimensional Linear Matrix Inequality (LMI) approach. Based on our recent work considering synthesis problems of stabilizing dynamic output feedback controllers which guarantee the internal stability of the dosed loop systems, we derive existence conditions and explicit formulas of two different dynamic output feedback H-infinity controllers, which guarantee the internal stability of the closed loop systems and a prescribed level of L-2 gain of closed loop systems. The derived dynamic output feedback H-infinity controllers can be interpreted as controllers which consist of memory state feedback controllers and memoryless/memory observers which have new observer structures. Next, we introduce a technique to reduce conditions for synthesis in the form of infinite-dimensional LMIs to the finite number of LMIs, and present. a feasible algorithm for synthesis of output feedback H-infinity controllers based on the finite-dimensional LMIs. Finally we demonstrate the efficacy of the proposed output feedback H-infinity controllers by numerical examples.

In this paper, we propose a geometric point of view for linear time invariant continuous systems and the method of identification based on this point of view. We also discuss the influence of observation noise on the evaluation of the system in our method based on the set membership approach. Then we demonstrate the proposed method of identification in experiment for a DC motor system.

In this paper, we consider a synthesis problem of delay-dependent memory state feedback control which stabilizes linear time-delay systems. First we derive conditions for stability analysis and controller synthesis in the form of infinite-dimensional (parameter-dependent) linear matrix inequalities (LMIs), while infinite dimensionality of the LMIs may lead to less conservative results, but makes the conditions difficult to use. Second we show a technique to reduce the infinite-dimensional LMIs to a finite number of LMIs. A numerical example is given to demonstrate out approach. (C) 2002 Elsevier Science Ltd. All rights reserved.

The load variation of the electro-hydraulic servosystem causes degradation of the control characteristic. This is because the flow characteristic of the flow control valve depends on the load condition. Here, we propose the flow calculation formula to have continues flow between turbulent and laminar flow so that compose the linear plant model with a scheduling parameter. Then, design gain scheduled controllers for the velocity and hydraulic force control.

In this paper, we consider the Lyapunov approach to adaptive identification for systems with unknown time invariant parameter. We describe the adaptive identification problem as stability analysis for linear parameter varying system, and then discuss the convergence of identification error and its convergence rate based on parameter dependent Lyapunov function.

This paper deals With a generalized H-infinity control attenuating initial-state uncertainties. An H-infinity control problem, which treats a mixed attenuation of disturbance and initial-state uncertainty for linear time-invariant systems in the infinite-horizon case, is examined. The mixed attenuation supplies H-infinity controls with good-transients and assures H-infinity controls of robustness against initial-state uncertainty. We derive a necessary and sufficient condition of the generalized mixed attenuation problem. Furthermore we apply this proposed method to a magnetic suspension system, and evaluate attenuation property of the proposed generalized H (infinity) control approach.

This paper presents active control of acoustic noise using radial basis function (RBF) networks and its digital signal processor (DSP) real-time implementation. The neural control system consists of two stages: first, identification (modeling) of secondary path of the active noise control using RBF networks and its learning algorithm, and secondly neural control of primary path based on neural model obtained in the first stage. A tapped delay fine is introduced in front of controller neural, and another tapped delay line is inserted between controller neural networks and model neural networks. An algorithm referred to as FX-RBF is proposed to account for secondary path effects of the control system arising in active noise control. The resulting algorithm turns out to be the filtered-X version of the standard RBF learning algorithm. We address centralized and decentralized controller configuration and their DSP implementation is carried out. Effectiveness of the neural controller is demonstrated by applying the algorithm to active noise control within a 3 dimension enclosure to generate quiet zones around error microphones. Results of the real-time experiments shows that 10-30 dB noise attenuation is obtained, are better than those obtained by classical least mean-square technique, such as FX-LMS.

This paper considers an analysis and synthesis problem of controllers for linear time-delay systems in the form of delay-dependent memory state feedback, and develops an Linear Matrix Inequality (LMI) approach. First, we present an existence condition and an explicit formula of controllers, which guarantee a prescribed level of L-2 gain of closed loop systems, in terms of infinite-dimensional LMIs. This result is rather general in the sense that it covers, as special cases, some known results for the cases of delay-independent/dependent and memoryless/memory controllers, while the infinity dimensionality of the LMIs makes the result difficult to apply. Second, we introduce a technique to reduce the infinite-dimensional LMIs to a finite number of LMIs, and present a feasible algorithm for synthesis of controllers based on the finite-dimensional LMIs.

This paper proposes a new LMI approach to analysis of linear systems depending on scheduling parameter in polynomial forms: we first propose a method to reduce the parameter dependent LMI condition, which characterizes internal stability and L2 gain, to the finite number of LMI conditions by introducing a convex polyhedron which includes a polynomial curve parameterized by scheduling parameter
next we propose a systematic procedure to construct the convex polyhedron. Our approach enable us to analyze L2 gain of linear systems with scheduling parameter in polynomial forms through computation of the finite number of LMIs. To show efficacy of our approach, we finally make a numerical experiment of L2 gain analysis for a gasturbine engine model which is described as a linear system with a scheduling parameter in polynomial form of two degree. © Oldenbourg Verlag.

For a nonlinear/linear system the disturbance to which is restricted to a finite domain, the reachable domain in the state space from a given initial state is called a state reachable set. Though some theoretical approaches have been proposed on investigating state reachable sets, it is difficult to evaluate the state reachable set actually for general nonlinear systems by using these approaches directly.<br>In this paper, we introduce a quadratic system based on a quadratic approximation for nonlinear systems. Then we propose an approach based on linear matrix inequalities to investigate the reachable set of the quadratic system the disturbance to which is restricted to inside of a unit disc. In numerical case study, we demonstrate efficacy of the proposed approach by evaluating the state reachable set actually for a given quadratic system.

In this paper, we define the kth-degree system which is regarded as Taylor series up to the kth-degree term for the nonlinear system, and propose an analysis technique of the semi-global L-2 gains based on the reachable set analysis for the kth-degree systems with the constraint sets on the disturbances. In this technique, the upper bounds of the semi-global L-2 gains are obtained by solving linear matrix-inequalities. We also illustrate the effectiveness of the proposed method with a numerical example.

We show a synthesis method of nonlinear state feedback control for input-affine polynomial-type nonlinear systems. The method consists of having this problem result in convex programming and solving linear matrix inequalities. To demonstrate efficiency of this method, we also show acomputer simulation for abilinear model of a continuous stirred tank reactor.

Quadratic stability analysis is one of the most effective technique to robust stability analysis for systems with parametric uncertainties. In ordinary quadratic stability analysis, quadratic stability of the system which consists of given system matrices (A-matrix), structure of parametric uncertainties, and a region of parametric uncertainties becomes a subject of discussion. In this paper, we evaluate the region of the parametric uncertainties for given system matrices and structure of parametric uncertainties, in which the system is quadratically stable. Though the evaluation is based on scaled H^∞ norm condition which is usually applied to quadratic stability analysis for parametric uncertain system, the evaluation dose not include scaling matrix.

''Optimum steering feel'', one goal of an automotive engineer, is related to how much information a vehicle obtains relating to the road. ''Road information'' is regarded as a frequency band of tire/steering wheel transmission characteristics, and in this paper we propose a method of supplying road information to the driver using a systematic control design with a ''generalized plant'' and ''H-infinity control''. In addition, the suitability and effectiveness of this Electric Power Steering (EPS) control system in supplying road information, derived from a greater freedom in designing the steering characteristics, is proven in experiments.

Recently many researches for Linear Parameter Varying Systems focus on the approach using a parameter-dependent Lyapunov function. Analysis and controller design for Linear Parameter Varying Systems are characterized by parameter-dependent Linear Matrix inequalities(LMIs). In this paper, pie propose an approach to solving parameter-dependent LMI conditions based on finite number of LMI conditions. The proposed method does not require any particular assumptions on the parameter dependence except continuity. We consider a class of Linear Parameter Varying Systems and apply the proposed technique on analysis of their L(2)gain. Finally we demonstrate its efficacy by numerical case study.

Using an extended quadratic Lyapunov function of the form V(x) = x(T)P(x)x, We consider La-gain analysis and state feedback control synthesis for input-affine polynomial type nonlinear systems, and derive Riccati type matrix inequality conditions that depend on a. We show that the solution P(x) can be given by solving linear matrix inequalities asa polynomial type matrix. We also determine the domain of internal stability. We finally show that the proposed method is effective through a numerical-example of bilinear systems.

In recent results on analysis and design of scheduled control for linear systems with scheduling parameter, parametrically-dependent LMI conditions characterize internal stability and L(2) gain performance. In this article, parametrically-dependent LMI condition is reduced to finite number of parametrically-independent LMI conditions. By applying this approach, actual analysis and actual design of the scheduled control for linear systems with scheduling parameter can be feasible by means of finite number of computation.

This paper is concerned with the finite horizon H_∞ filtering problem of linear discrete-time, time-varying systems using a direct approach based on the completing-the-square. We derive a necessary and sufficient condition for the existence of the H_∞ filters, and give the parametrization of all linear H_∞ filters. In particular, the time-updating H_∞ filtering algorithm is explicitly shown. Furthermore, we investigate a possibility of the real-time application of the H_∞ filters to a robotic visual tracking system. The simulation results show that the derived H_∞ filtering algorithm is quite effective for the robotic visual tracking applications.

A robust stabilization problem is discussed for a system with delays in control. We derive a robust stabilizing law against additive perturbations. Then, motivated by the feature of predictive controllers, we investigate the structure of robust stabilizing law and provide some interpretations on the relation between the value of time delay and the achievable margin of robust stabilizability.

In the control of the actual plant, there exits a difference between output of compensator and control input momentarily. This is caused by mechanical constraint on the actuator like saturation and rate limit, and constraint on the control input to protect the plant in the aircraft engine controls etc. Difference between output of compensator with integral element and control input causes windup phenomenon and gives adverse effects to the control performance. One of the techniques to prevent the above phenomenon is anti-windup and bumpless transfer technique.<br>In this paper, we derive sufficient condition of robust stability for the system consisting of the plant with linear time invariant multiplicative uncertainty, compensator, constraint on the control input, and anti-windup and bumpless transfer block. Then, we propose a new algorism of anti-windup and bumpless transfer block synthesis which directly uses this stability condition. In numerical example, we design the anti-windup and bumpless transfer block to a given system, and evaluate its performance by computer simulation.

A robust stabilization problem is discussed for time delay systems. By introducing an indefinite Riccati type operator equation for time delay systems, we propose a design method of robust stabilizing control law against the parametric uncertainties, which occur in lumped parameter element and in all types of delay element. In the derivation of the control law, the key point is that we take a combined approach; one is an internal approach based on a Lyapunov type operator equation and another is an external approach based on small-gain theorem. This twofold approach first enables us to deal with the uncertainties of time delay systems in a unified way.

In the H^∞ output feedback problem, there are two types of central controllers, which play a central role in characterizing all controllers achieving disturbance attenuation in the sense of the H^∞-norm.<br>In this paper, we provide a unified game-theoretic interpretation to the both types of central controllers. By employing completing the square argument of particular quadratic forms, we clarify that the two types of central controllers form different saddle points together with the corresponding worst-case disturbances. In the derivation of each saddle point, the difference is in the particular choice of quadratic-form functionals to which we apply the completing the square argument.<br>Then generalizing the approaches established here, we secondly consider a mixed attenuation problem of disturbances and initial-uncertainties. The trade-off between the attenuating the disturbances and the initial-uncertainties are characterized by the solution to the filtering Riccati equation.

A robust stability problem for time delay systems is discussed by using the properties of the Lyapunov type operator equation. We propose a method to check the robust stability against the parameter perturbations which occur in both the lumped parameter element and the distributed delay element.

A robust stabilization problem is discussed for time delay systems. By introducing an indefinite Riccati type operator equation for time delay systems, we propose a design method of robust stabilizing control law against the parametric uncertainties, which occur in lumped parameter element and in all types of delay element. In the derivation of the control law, the key point is that we take a twofold approach; one is an internal approach based on Lyapunov type operator equation and another is an external approach based on small-gain theorem. This twofold approach first enable us to deal the uncertainties of time delay systems in a unified way.

A robust stabilization problem is discussed for time delay systems. We propose a design method of robust stabilizing control law by introducing an indefinite Riccati type operator equation defined for time delay systems. The parameter perturbations are assumed to occur in all types of delay elements; in lumped parameter element, in distributed delay element and in point delay element.