Event-Triggered Sliding-Mode Control for Polynomial Fuzzy Singular Systems

Feng, Zhiguang; Yang, Yang; Wu, Ligang

doi:10.1109/tsmc.2022.3222175

Cited by 7 publications

(2 citation statements)

References 46 publications

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“…The primary aim of this paper is to develop control algorithm to design the event-triggered observer-based controller for FSSs, formulated in (5), so that the feedback system ( 6) is admissible and achieves a strictly (Q, S, R)-βdissipative performance.…”

Section: Lemma 1 ([10]) Let Us Consider the Double Fuzzy Summation-ba...mentioning

confidence: 99%

“…Meanwhile, the event-triggered mechanism offers an efficient control strategy that can reduce data transmission and computation burden, as control actions are only updated on certain events. Motivated by this advantage, various related works have been reported in the field of FSSs as well [15,5,4]. As a representative study, [24] resolved the control problem to design an observer for continuous-time Takagi-Sugeno fuzzy systems with respect to event-triggered transmission and asynchronous phenomenon.…”

Section: Introductionmentioning

confidence: 99%

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Admissibility and event-triggered dissipative observer-based stabilization of discrete-time T-S fuzzy singular systems via fuzzy Lyapunov functions

Nguyen,

Kim

2023

Preprint

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This paper presents a new method to design an event-triggered dissipative observer-based control for discrete-time Takagi-Sugeno fuzzy singular systems by handling admissibility, dissipativity, observer-based control, and event-triggered data problems all in one. In particular, the proposed method has the advantage of being able to realize a one-step design framework that simultaneously designs both fuzzy observer and controller gains without using any iterative search algorithms. Furthermore, the proposed method provides the flexibility to set the fuzzy event weighting matrix in conjunction with other variables and supports the performance improvement of control systems by using a fuzzy Lyapunov function. Not only that, different from other eventtriggered output-feedback control techniques, the event generation function of this paper is constructed based on actual system outputs rather than estimated states so that estimation errors are not reflected in the event-triggered mechanism. Finally, two illustrative examples are given to verify the effectiveness of the proposed method.

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Section: Lemma 1 ([10]) Let Us Consider the Double Fuzzy Summation-ba...mentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Admissibility and event-triggered dissipative observer-based stabilization of discrete-time T-S fuzzy singular systems via fuzzy Lyapunov functions

Nguyen,

Kim

2023

Preprint

View full text Add to dashboard Cite

show abstract

Admissibility and event-triggered dissipative observer-based stabilization of discrete-time T-S fuzzy singular systems via fuzzy Lyapunov functions

Nguyen,

Kim

2024

Nonlinear Dyn

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Event-triggered model-free adaptive control for nonlinear systems using intuitionistic fuzzy neural network: simulation and experimental validation

Abd-Elhaleem,

Hussien,

Hamdy

et al. 2023

Complex Intell. Syst.

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This article presents model-free adaptive control based on an intuitionistic fuzzy neural network for nonlinear systems with event-triggered output. Essentially, model-free adaptive control (MFAC) is constructed by establishing an online approximate model of the controlled system using the pseudo-partial derivative (PPD) form. By the proposed scheme, first, an intuitionistic fuzzy neural network (IFNN) is developed as an estimator for time-varying PPD in both compact-form dynamic linearization (CFDL) and partial-form dynamic linearization (PFDL) for the MFAC technique. Second, two periodic event-triggered output methods are integrated with the proposed IFNN-based MFAC in both forms to save communication resources and reduce the computation burden and energy consumption. Based on the Lyapunov theory and BIBO stability approach, necessary conditions are established to guarantee the convergence of the adaptive law of the IFNN controller and the boundary of the tracking error of the closed loop system. Third, regarding the feasibility and the effectiveness of the developed control method, two simulation examples including the continuous stirred-tank reactor (CSTR) system and the heat exchanger system are given. Finally, the practical validation of the proposed data-driven control method is conducted via the speed control of a DC motor.

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Event-Triggered Sliding-Mode Control for Polynomial Fuzzy Singular Systems

Cited by 7 publications

References 46 publications

Admissibility and event-triggered dissipative observer-based stabilization of discrete-time T-S fuzzy singular systems via fuzzy Lyapunov functions

Admissibility and event-triggered dissipative observer-based stabilization of discrete-time T-S fuzzy singular systems via fuzzy Lyapunov functions

Admissibility and event-triggered dissipative observer-based stabilization of discrete-time T-S fuzzy singular systems via fuzzy Lyapunov functions

Event-triggered model-free adaptive control for nonlinear systems using intuitionistic fuzzy neural network: simulation and experimental validation

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