Complex performance control using sliding mode fuzzy approach for discrete-time nonlinear systems via T-S fuzzy model with bilinear consequent part

Chang, Wen‐Jer; Hsu, Feng-Ling; Ku, Cheung-Chieh

doi:10.1007/s12555-016-9404-3

Cited by 14 publications

(4 citation statements)

References 44 publications

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“…only contain friction term, we can consider fuzzy compensation for approximate friction [26,27,38]. Due to the fact that is only related to the speed signal, the fuzzy system for approximate friction can be expressed aŝ(̇| ), and we can design control law according to traditional fuzzy compensation controller design method like (14), (18), and (20) [39,40].…”

Section: Fuzzy Compensation Smc For Friction When ( )mentioning

confidence: 99%

Sliding Mode Control with Adaptive Fuzzy Compensation for Uncertain Nonlinear System

Wang

Zhang

2018

Mathematical Problems in Engineering

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Fuzzy sliding mode control as a robust and intelligent nonlinear control technique is proposed to control processes with severe nonlinearity and unknown models. This paper proposes a new adaptive tracking fuzzy sliding mode controller for nonlinear systems in the presence of fuzzy compensation. The main contribution of the proposed method is that the fuzzy system is used to realize the adaptive approximation of the unknown part of the model, and the fuzzy gain can be reduced effectively. The fuzzy self-adaptive rate is derived through the Lyapunov method, and the stability and convergence of the whole closed-loop system are guaranteed by adjusting the adaptive weight value. The performance of the proposed approach is evaluated for double joint rigid manipulator problems. The simulation results illustrate the effectiveness of our proposed controller.

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Section: Fuzzy Compensation Smc For Friction When ( )mentioning

confidence: 99%

Sliding Mode Control with Adaptive Fuzzy Compensation for Uncertain Nonlinear System

Wang

Zhang

2018

Mathematical Problems in Engineering

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“…After converting into a class of T–S fuzzy models, the analysis and synthesis of the nonlinear systems become easy and the conventional linear system theories could be utilized. Moreover, many achievements have been made in the research of T–S fuzzy systems, for instance References 8‐14. A stabilization issue for the discrete‐time nonlinear system against external disturbance, multiplicative noises, and multiple constraints was researched in accordance with the definition of Lyapunov stability in Reference 8.…”

Section: Introductionmentioning

confidence: 99%

“…Moreover, many achievements have been made in the research of T–S fuzzy systems, for instance References 8‐14. A stabilization issue for the discrete‐time nonlinear system against external disturbance, multiplicative noises, and multiple constraints was researched in accordance with the definition of Lyapunov stability in Reference 8. In Reference 10, the stability of sampled data T–S fuzzy control systems subject to packet dropouts was researched by sampling‐dependent time‐varying Lyapunov function.…”

Section: Introductionmentioning

confidence: 99%

Robust reliableH_∞optimization control for uncertain discrete‐time Takagi–Sugeno fuzzy systems with time‐varying delay

Sun

Zhang

et al. 2021

Optim Control Appl Methods

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In this article, the problems of robust reliable H∞ optimization control for discrete‐time nonlinear systems with or without time‐delay subject to faults are investigated. A static state feedback controller is explored for Takagi–Sugeno fuzzy systems against nonlinear dynamics, exogenous disturbances, and model uncertainties. In contrast to the design of conventional controllers, the proposed controller is easier and more flexible. The Lyapunov function is utilized to assure the stability of the closed‐loop systems. Besides, linear matrix inequalities are utilized to derive the sufficient conditions by MATLAB toolbox. Finally, two simulation examples are shown to validate the feasibility of the suggested approach.

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“…The T‐S fuzzy model control method has also been widely applied in many practical industrial systems recently. Significant efforts have been devoted to study the analysis and synthesis problems of T‐S fuzzy control systems [4–7].…”

Section: Introductionmentioning

confidence: 99%

Fuzzy controller design for nonlinear singular systems with external noises subject to passivity constraints

Chang

Varadarajan

2020

Asian Journal of Control

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This paper applies the state derivative feedback method and proportional plus derivative state feedback method to design the fuzzy controllers for the nonlinear singular systems with external noises. The Takagi‐Sugeno fuzzy modeling technology is employed in this paper to represent the nonlinear singular systems with external noise. Considering the singular Takagi‐Sugeno fuzzy model, the passivity constraint is chosen to treat the external noises for the controlled systems. By using the parallel distributed compensation method, the fuzzy controller is designed to satisfy the Lyapunov stability conditions and passivity constraints simultaneously. These sufficient conditions can be effectively solved in terms of linear matrix inequalities, which can be solved via the convex optimization technique. At last, some numerical examples are provided to verify the applicability and effectivity of the proposed fuzzy controller design methods.

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Complex performance control using sliding mode fuzzy approach for discrete-time nonlinear systems via T-S fuzzy model with bilinear consequent part

Cited by 14 publications

References 44 publications

Sliding Mode Control with Adaptive Fuzzy Compensation for Uncertain Nonlinear System

Sliding Mode Control with Adaptive Fuzzy Compensation for Uncertain Nonlinear System

Robust reliableH_∞optimization control for uncertain discrete‐time Takagi–Sugeno fuzzy systems with time‐varying delay

Fuzzy controller design for nonlinear singular systems with external noises subject to passivity constraints

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Complex performance control using sliding mode fuzzy approach for discrete-time nonlinear systems via T-S fuzzy model with bilinear consequent part

Cited by 14 publications

References 44 publications

Sliding Mode Control with Adaptive Fuzzy Compensation for Uncertain Nonlinear System

Sliding Mode Control with Adaptive Fuzzy Compensation for Uncertain Nonlinear System

Robust reliableH∞optimization control for uncertain discrete‐time Takagi–Sugeno fuzzy systems with time‐varying delay

Fuzzy controller design for nonlinear singular systems with external noises subject to passivity constraints

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Robust reliableH_∞optimization control for uncertain discrete‐time Takagi–Sugeno fuzzy systems with time‐varying delay