Fuzzy Controller Design via the Inverse Solution of Lyapunov Equations

2003 ◽  
Vol 125 (1) ◽  
pp. 42-47 ◽  
Author(s):  
Wen-Jer Chang
Keyword(s):  
Fuzzy Controller ◽  
Controller Design ◽  
Design Method ◽  
Fuzzy Model ◽  
Lyapunov Equation ◽  
Inverse Solution ◽  
Lyapunov Equations ◽  
Common Lyapunov Function ◽  
Compensation Technique ◽  
Takagi Sugeno

In this paper, a fuzzy control design method is be developed for the plant model whose structure is represented by the Takagi-Sugeno fuzzy model. In each rule of the Takagi-Sugeno fuzzy model, the system is characterized by linear dynamics given in the controllability canonical form. Replacing the Lyapunov inequality with a Lyapunov equation for stability analysis, the proposed method will make use of the inverse solution of Lyapunov equations to obtain a common Lyapunov function for all the subsystems. Based on this solution, the fuzzy controller can be constructed by using the parallel distributed compensation technique.

scholarly journals Actuator Saturated Fuzzy Controller Design for Interval Type-2 Takagi-Sugeno Fuzzy Models with Multiplicative Noises

Processes ◽  
2021 ◽  
Vol 9 (5) ◽  
pp. 823
Author(s):  
Wen-Jer Chang ◽  
Yu-Wei Lin ◽  
Yann-Horng Lin ◽  
Chin-Lin Pen ◽  
Ming-Hsuan Tsai
Keyword(s):  
Nonlinear Systems ◽  
Fuzzy Controller ◽  
Controller Design ◽  
Actuator Saturation ◽  
Design Method ◽  
Fuzzy Model ◽  
The Stability ◽  
Interval Type ◽  
Takagi Sugeno

In many practical systems, stochastic behaviors usually occur and need to be considered in the controller design. To ensure the system performance under the effect of stochastic behaviors, the controller may become bigger even beyond the capacity of practical applications. Therefore, the actuator saturation problem also must be considered in the controller design. The type-2 Takagi-Sugeno (T-S) fuzzy model can describe the parameter uncertainties more completely than the type-1 T-S fuzzy model for a class of nonlinear systems. A fuzzy controller design method is proposed in this paper based on the Interval Type-2 (IT2) T-S fuzzy model for stochastic nonlinear systems subject to actuator saturation. The stability analysis and some corresponding sufficient conditions for the IT2 T-S fuzzy model are developed using Lyapunov theory. Via transferring the stability and control problem into Linear Matrix Inequality (LMI) problem, the proposed fuzzy control problem can be solved by the convex optimization algorithm. Finally, a nonlinear ship steering system is considered in the simulations to verify the feasibility and efficiency of the proposed fuzzy controller design method.

scholarly journals Fuzzy Controllers for Nonaffine-in-Control Singularly Perturbed Switched Systems

2015 ◽  
Vol 2015 ◽  
pp. 1-11 ◽  
Author(s):  
Linna Zhou ◽  
Qianjin Wang ◽  
Xiaoping Ma ◽  
Chunyu Yang
Keyword(s):  
Switched Systems ◽  
Fuzzy Controller ◽  
Controller Design ◽  
Design Method ◽  
Singularly Perturbed ◽  
Dynamic State ◽  
Linear Matrix ◽  
Closed Loop System ◽  
Stability Bound ◽  
Takagi Sugeno

This paper investigates the problem of fuzzy controller design for nonaffine-in-control singularly perturbed switched systems (NCSPSSs). First, the NCSPSS is approximated by Takagi-Sugeno (T-S) models which include not only state but also control variables in the premise part of the rules. Then, a dynamic state feedback controller design method is proposed in terms of linear matrix inequalities. Under the controller, stability bound estimation problem of the closed-loop system is solved. Finally, an example is given to show the feasibility and effectiveness of the obtained methods.

DELAYED FUZZY CONTROLLER DESIGN FOR HYPERCHAOS WITH APPLICATION TO HYPERCHAOTIC CHEN'S SYSTEM

2007 ◽  
Vol 18 (07) ◽  
pp. 1095-1105 ◽  
Author(s):  
XINGWEN LIU ◽  
XIN GAO
Keyword(s):  
Fuzzy Controller ◽  
Controller Design ◽  
Fuzzy Model ◽  
Linear Matrix ◽  
Delayed State Feedback ◽  
Delay Dependent ◽  
Takagi Sugeno ◽  
Compensation Design ◽  
Hyperchaotic Systems ◽  
Control Criterion

Studied in this paper is the control problem of hyperchaotic systems. By combining Takagi–Sugeno (T–S) fuzzy model with parallel distributed compensation design technique, we propose a delay-dependent control criterion via pure delayed state feedback. Because the result is expressed in terms of linear matrix inequalities (LMIs), it is quite convenient to check in practice. Based on this criterion, a procedure is provided for designing fuzzy controller for such systems. This method is a universal one for controlling continuous hyperchaotic systems. As illustrated by its application to hyperchaotic Chen's system, the controller design is quite effective.

APPLICATION AND ROBUSTNESS DESIGN OF FUZZY CONTROLLER FOR RESONANT AND CHAOTIC SYSTEMS WITH EXTERNAL DISTURBANCE

2005 ◽  
Vol 13 (03) ◽  
pp. 281-295 ◽  
Author(s):  
FENG-HSIAG HSIAO ◽  
WEI-LING CHIANG ◽  
CHENG-WU CHEN ◽  
SHENG-DONG XU ◽  
SHIH-LIN WU
Keyword(s):  
Chaotic Systems ◽  
Fuzzy Controller ◽  
Controller Design ◽  
Design Method ◽  
Direct Method ◽  
External Disturbance ◽  
Approximation Error ◽  
Fuzzy Model ◽  
Linear Matrix ◽  
Resonant Systems

A robustness design of fuzzy control via model-based approach is proposed in this paper to overcome the effect of approximation error between nonlinear system and Takagi-Sugeno (T-S) fuzzy model. T-S fuzz model is used to model the resonant and chaotic systems and the parallel distributed compensation (PDC) is employed to determine structures of fuzzy controllers. Linear matrix inequality (LMI) based design problems are utilized to find common definite matrices P and feedback gains K satisfying stability conditions derived in terms of Lyapunov direct method. Finally, the effectiveness and the feasibility of the proposed controller design method is demonstrated through numerical simulations on the chaotic and resonant systems.

Further Results on T-S Fuzzy Controller Design Subject to Input Constraint

2008 ◽  
Vol 12 (2) ◽  
pp. 190-197 ◽  
Author(s):  
Hugang Han ◽  
Keyword(s):  
Fuzzy Controller ◽  
Controller Design ◽  
Fuzzy Model ◽  
State Feedback Control ◽  
Linear Matrix ◽  
Input Constraint ◽  
Initial State ◽  
Control Gain ◽  
Matrix Variable ◽  
Takagi Sugeno

In general, when using the Takagi-Sugeno (T-S) fuzzy model to develop a control system, the state feedback control gain can be obtained by solving some linear matrix inequalities (LMIs). In this paper, we consider a class of nonlinear systems with input constraint (saturation). To obtain the control gain, we require to employ certain extra LMIs besides the general ones. As a result, all the LMIs are more conservative. At the same time, one of the extra LMIs confines the initial state to a region, which is referred to as an ellipsoid, and is relevant to a matrix variable in the LMIs. Therefore, the goals of this paper are: 1) making the ellipsoid as large as possible so that the initial state can be confined to the region easily and; 2) making all the LMIs more feasible to obtain the control gain.

ANTICONTROL OF CHAOS FOR A CONTINUOUS-TIME TAKAGI–SUGENO FUZZY SYSTEM VIA LOCAL TIME-DELAY FEEDBACK

2005 ◽  
Vol 15 (12) ◽  
pp. 3883-3894 ◽  
Author(s):  
TAEK RYONG KIM ◽  
YOUNG HOON JOO ◽  
JIN BAE PARK ◽  
GUANRONG CHEN
Keyword(s):  
Time Delay ◽  
Discrete Time ◽  
Continuous Time ◽  
Fuzzy System ◽  
Closed Loop ◽  
Fuzzy Controller ◽  
Design Method ◽  
Fuzzy Model ◽  
Takagi Sugeno ◽  
Systematic Control

In this paper, a simple and systematic control design method is proposed for making a continuous-time Takagi–Sugeno (T–S) fuzzy system chaotic. The concept of parallel distributed compensation is employed to determine the structure of a fuzzy controller from a T–S fuzzy model. The fuzzy controller makes the T–S fuzzy model, which could be stable or unstable, bounded and chaotic. The verification of chaos in the closed-loop T–S fuzzy system is done by the following procedure. First, we establish an asymptotically approximate relationship between a continuous-time T–S fuzzy system with time-delay and a discrete-time T–S fuzzy system. Then, we verify the chaos in the closed-loop T–S fuzzy system by applying the Marotto theorem to its associated discrete-time T–S fuzzy system. The generated chaos is in the sense of Li and Yorke. Two examples are given to show that this methodology is simple and effective for anticontrol of chaos for a continuous-time T–S fuzzy system.

Discrete Fuzzy Controller Design for Achieving Common State Covariance Assignment

2004 ◽  
Vol 126 (3) ◽  
pp. 627-632 ◽  
Author(s):  
Wen-Jer Chang ◽  
Chong-Cheng Shing
Keyword(s):  
Feedback Control ◽  
Covariance Matrix ◽  
Output Feedback ◽  
Fuzzy Systems ◽  
Fuzzy Controller ◽  
Controller Design ◽  
Fuzzy Model ◽  
Output Feedback Control ◽  
Control Approach ◽  
Takagi Sugeno

In this paper, a method is developed to find the output feedback fuzzy controllers for assigning a common state covariance matrix of discrete Takagi–Sugeno (T–S) fuzzy systems. The fuzzy control approach developed in this paper is based on the concept of Parallel Distributed Compensation (PDC). For each rule of the discrete T–S fuzzy model, it shows how to parameterize the static linear output feedback control gains to achieve a common state covariance matrix for each subsystem. Finally, a numerical example is provided to verify the effects of the proposed method.

scholarly journals Further results on robust fuzzy dynamic systems with LMI D-stability constraints

2014 ◽  
Vol 24 (4) ◽  
pp. 785-794 ◽  
Author(s):  
Wudhichai Assawinchaichote
Keyword(s):  
Dynamic Systems ◽  
Fuzzy Controller ◽  
Sufficient Conditions ◽  
Fuzzy Model ◽  
Local System ◽  
Linear Matrix ◽  
Fuzzy Modelling ◽  
Ts Fuzzy Model ◽  
Input Noise ◽  
Takagi Sugeno

Abstract This paper examines the problem of designing a robust H∞ fuzzy controller with D-stability constraints for a class of nonlinear dynamic systems which is described by a Takagi-Sugeno (TS) fuzzy model. Fuzzy modelling is a multi-model approach in which simple sub-models are combined to determine the global behavior of the system. Based on a linear matrix inequality (LMI) approach, we develop a robust H∞ fuzzy controller that guarantees (i) the L2-gain of the mapping from the exogenous input noise to the regulated output to be less than some prescribed value, and (ii) the closed-loop poles of each local system to be within a specified stability region. Sufficient conditions for the controller are given in terms of LMIs. Finally, to show the effectiveness of the designed approach, an example is provided to illustrate the use of the proposed methodology.

scholarly journals Dissipativity-Based Controller Design for Time-Delayed T-S Fuzzy Switched Distributed Parameter Systems

Complexity ◽  
2018 ◽  
Vol 2018 ◽  
pp. 1-11 ◽  
Author(s):  
Xiaona Song ◽  
Mi Wang ◽  
Shuai Song ◽  
Jingtao Man
Keyword(s):  
Fuzzy Controller ◽  
Controller Design ◽  
Sufficient Conditions ◽  
Fuzzy Model ◽  
Distributed Parameter Systems ◽  
Linear Matrix ◽  
Distributed Parameter ◽  
Time Varying Delay ◽  
Closed Loop Systems ◽  
Control Gain

This paper studies fuzzy controller design problem for a class of nonlinear switched distributed parameter systems (DPSs) subject to time-varying delay. Initially, the original nonlinear DPSs are accurately described by Takagi-Sugeno fuzzy model in a local region. On the basis of parallel distributed compensation technique, mode-dependent fuzzy proportional and fuzzy proportional-spatial-derivative controllers are constructed, respectively. Subsequently, using single Lyapunov-Krasovskii functional and some matrix inequality methods, sufficient conditions that guarantee the stability and dissipativity of the closed-loop systems are presented in the form of linear matrix inequalities, which allow the control gain matrices to be easily obtained. Finally, numerical examples are provided to demonstrate the validity of the designed controllers.

Sign in / Sign up

Export Citation Format

Share Document