• Journal of the Korea Institute of Information and Communication Engineering
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• v.17 no.6
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• pp.1399-1408
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• 2013

This paper proposes a new $H_{\infty}$ T-S fuzzy controller with a novel integral control for induction motors which have nonlinear dynamics. The $H_{\infty}$ T-S fuzzy controller is used for the nonlinearity and robustness and weighted integral is used for tracking problem and control performance. A T-S Fuzzy controller is the fuzzy combination of local linear controllers considering the overall stability, and LMI(Linear Matrix Inequlity) is used for determining the gains of linear controllers. The tracking problem of an induction motor is changed into regulator problem by introducing the integral control technique with weighting factor, diminishing the conservatism of $H_{\infty}$ T-S fuzzy controller.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.15 no.7
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• pp.1447-1456
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• 2011

In this paper, we propose a T-S fuzzy feedback linearization method for controlling a non-linear system with multi-input, and the method is applied for trajectory tracking control of wheeled mobile robot. First, an error dynamic equation of wheeled mobile robot is represented by a T-S fuzzy model, and then the T-S fuzzy model is transformed to a linear control system through the nonlinear fuzzy coordinate change and the nonlinear state feedback input. Simulation results showed that the trajectory tracking controller by using the proposed multi-input feedback linearization method gives better performance than the trajectory tracking controller by using the PDC(Parallel Distributed Compensation) method for controlling the T-S Fuzzy system.

• International Journal of Control, Automation, and Systems
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• v.5 no.3
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• pp.349-354
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• 2007

This paper considers the problem of designing static output feedback controllers for nonlinear systems represented by Takagi-Sugeno (T-S) fuzzy models. Based on linear matrix inequality technique, a new method is developed for designing fuzzy stabilizing controllers via static output feedback. Furthermore, the result is also extended to $H_{\infty}$ control. Examples are given to illustrate the effectiveness of the proposed methods.

• Journal of Institute of Control, Robotics and Systems
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• v.22 no.7
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• pp.496-501
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• 2016

This paper presents a design method of non-parallel distributed compensation (non-PDC) static output feedback controller for continuous- and discrete-time T-S fuzzy systems. The existence condition of static output feedback control law is represented in terms of linear matrix inequalities (LMIs). The proposed sufficient stabilizing condition does not need any transformation matrices and equality constraints and is less conservative than the previous result of [21].

• Transactions on Control, Automation and Systems Engineering
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• v.3 no.2
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• pp.95-105
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• 2001

In this paper, in order to control uncertain chaotic system, an adaptive fuzzy control(AFC) scheme is developed for the multi-input/multi-output plants represented by the Takagi-Sugeno(T-S) fuzzy models. The proposed AFC scheme provides robust tracking of a desired signal for the T-S fuzzy systems with uncertain parameters. The developed control law and adaptive law guarantee the boundedness of all signals in the closed-loop system. In addition, the chaotic state tracks the state of the stable reference model(SRM) asymptotically with time for any bounded reference input signal. The suggested AFC design technique is applied for the control of an uncertain Lorenz system based on T-S fuzzy model such as stabilization, synchronization and chaotic model following control(CMFC).

• Journal of Institute of Control, Robotics and Systems
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• v.21 no.6
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• pp.560-564
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• 2015

This paper presents a design method of a static output feedback controller for continuous T-S fuzzy systems via parallel distributed compensation (PDC). The existence condition of a set of static output feedback gains is represented in terms of linear matrix inequalities (LMIs). The sufficient condition presented here does not need any transformation matrices and equality constraints and is less conservative than the previous results seen in [20].

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2004.04a
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• pp.559-562
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• 2004

In this paper, a new dual-rate digital control technique for the Takagi-Sugeno (T-S) fuzzy system is suggested. The proposed method takes account of the stabilizablity of the discrete-time T-S fuzzy system at the fast-rate sampling points. Our main idea is to utilize the lifted control input. The proposed approach is to obtain the dual-rate discrete-time T-S fuzzy system by discretizing the overall dynamics of the T-S fuzzy system with the lifted control, and then to derive the sufficient conditions for the stabilization in the sense of the Lyapunov asymptotic stability for this system.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 1998.06a
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• pp.331-336
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• 1998

A systematic design method for PDC(Parallel Distributed Compensation)-type continuous time Takagi-Sugeno(T-S in short) fuzzy control systems which have inaccessible states is developed in this paper. Reduced-dimensional fuzzy state estimator is introduced from existing T-S fuzzy model using the PDC structure of Wang et al. [1] LMI(Linear Matrix Inequalities) problems which represent the stabililty of the reduced-dimensional fuzzy state estimator are derived. Pole placement constraints idea for each rules is adopted to determine the estimator gains and they are also revealed as LMI problems. these LMI problems are combined with Joh et al's [7][8] LMI problems for PDC -type continuous time T-S fuzzy controller design to yield a systematic design method for PDC -type continuous time T-S fuzzy control systems which have inaccessible states.

• Proceedings of the IEEK Conference
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• 2009.05a
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• pp.390-392
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• 2009

This paper is concerned with the stabilization problem of nonlinear networked control systems with time-delay via Takagi-Sugeno(T-S) fuzzy control approach. The T-S fuzzy models are employed to represent nonlinear systems with Markovian jump parameters and time-delay. The purpose of this paper is to design a fuzzy controller such that the closed-loop Markovian jump fuzzy system is stochastically stable. Based on a stocastic Lyapunov function, stabilization sufficient conditions using a mode-independent fuzzy controller are derived for the Markovian jump fuzzy system in terms of Linear Matrix Inequalities(LMIs). Finally, a simulation example is presented to illustrate the effectiveness of the proposed method.

• Proceedings of the IEEK Conference
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• 2009.05a
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• pp.329-331
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• 2009

This paper is concerned with the stabilization problem of nonlinear networked control systems with time-delay via Takagi-Sugeno(T-S) fuzzy control approach. The T-S fuzzy models are employed to represent nonlinear systems with Markovian jump parameters and time-delay. The purpose of this paper is to design a fuzzy controller such that the closed-loop Markovian jump fuzzy system is stochastically stable. Based on a stocastic Lyapunov function, stabilization sufficient conditions using a mode-independent fuzzy controller are derived for the Markovian jump fuzzy system in terms of Linear Matrix Inequalities(LMIs). Finally, a simulation example is presented to illustrate the effectiveness of the proposed method.