A novel adaptive event‐triggered scheme for network descriptor systems with randomly occurring uncertainties and nonlinearities

Wang, Yu‐Zhong; Zhang, Tie; Cui, Tong; Ma, Limin; Ren, Junchao

doi:10.1002/acs.3190

Cited by 3 publications

(2 citation statements)

References 37 publications

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“…Although the above‐mentioned ETC schemes can be used to achieve the required performance, the transmitted sampled‐data are still a lot when the studied system is stable, since their event‐triggered parameters are constants. In recent years, an adaptive ETC scheme has drawn much attention, where its event‐triggered parameter can be adaptively adjusted, and many important results have been proposed in References 14‐19. However, the adaptive event‐triggered parameters were functions of state variable or the measurement output in References 14‐16 and 20.…”

Section: Introductionmentioning

confidence: 99%

Adaptive event‐triggered quantized H∞ fuzzy filtering for T‐S fuzzy systems via fuzzy Lyapunov–Krasovskii functional method

Chen

2022

Adaptive Control & Signal

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This article is concerned on the problem of adaptive event-triggered quantized H ∞ fuzzy filtering for networked T-S fuzzy control systems under imperfect premise matching. First, a novel adaptive event-triggered communication scheme for networked fuzzy control systems is built to save more limited network bandwidth, where the event-triggered parameter is changed with the output fluctuation. Second, a fuzzy filter with the imperfect premise matching is designed. Under consideration of event-triggered scheme and quantization method, an unified filtering error model is well constructed, which contains time delay and parameter uncertainties. Then, a new augmented fuzzy Lyapunov-Krasovskii functional including a fuzzy Lyapunov matrix and a delay product term is established, and sufficient conditions are derived to guarantee the asymptotic stability of the filtering error system with a given H ∞ performance. Moreover, the corresponding filter can be designed by solving a set of linear matrix inequalities. Finally, a numerical example is put forward to illustrate the effectiveness and advantages of the proposed method.

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Section: Introductionmentioning

confidence: 99%

Adaptive event‐triggered quantized H∞ fuzzy filtering for T‐S fuzzy systems via fuzzy Lyapunov–Krasovskii functional method

Chen

2022

Adaptive Control & Signal

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“…Follow-up research on the uncertain singular systems has been carried out in [22]- [24] by the observerbased control method, and in [25], [26] for the filtering methods, in these methods, the boundary assumptions of uncertainties and disturbances are necessary. In [27], the problem of event-triggered H ∞ control for the singular systems with randomly occurring uncertainty and nonlinearity was investigated. However, all of the above papers always assume that the uncertainties are known or bounded, and the robust control problem was solved by the time domain method, the robust stability conditions were proposed in terms of linear matrix inequalities (LMIs).…”

Section: Introductionmentioning

confidence: 99%

Robust Control for Singular Systems Based on the Uncertainty and Disturbance Estimator

Yang

2021

IEEE Access

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This paper is devoted to investigating the robust control problem for a class of singular systems with model structure uncertainty and external disturbance. Firstly, the uncertainty and disturbance estimator (UDE)-based robust control law is established for uncertain singular systems. Secondly, the twodegree-of-freedom (2DOF) nature of singular systems under the UDE-based robust controller is revealed, which shows that asymptotic reference tracking and disturbance rejection are decoupled. Additionally, on the basis of the small-gain theorem, sufficient conditions are established to ensure robust stability of the closed-loop system and to achieve asymptotic reference tracking and disturbance rejection. Finally, three numerical examples and a practical application to the multi-agent supporting systems are provided to illustrate the validity of the methods proposed.

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Non‐fragile control for dynamic event‐triggered networked systems with randomly occurring nonlinearities

Liu

Yao

et al. 2022

Math Methods in App Sciences

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This article focuses on the issue of non‐fragile control for a networked control systems (NCSs) with randomly occurring nonlinearities, where an advanced dynamic event‐triggered mechanism (DETM) is introduced. First, an improved DETM transmission strategy for NCSs is proposed. Based on the dynamic error of the system, the improved DETM can adaptively adjust the threshold to control the transmission of signals. The balance of the network bandwidth and control performance is excellently regulated by the adaptive threshold rather than a predetermined constant. Second, by taking the networked‐induced delay, DETM, randomly occurring nonlinearities and controller gain perturbation into consideration, a nonlinear system model is established. Next, sufficient stability conditions that can guarantee the mean‐square asymptotical stability are obtained based on the novel two‐side Lyapunov‐Krasovskii functional (LKF) and second‐order generalized free‐matrix‐based integral inequality (GFMBII), which contains more system information and can provide less conservative results. Finally, two numerical examples are presented to verify the advantages of the proposed method.

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A novel adaptive event‐triggered scheme for network descriptor systems with randomly occurring uncertainties and nonlinearities

Cited by 3 publications

References 37 publications

Adaptive event‐triggered quantized H∞ fuzzy filtering for T‐S fuzzy systems via fuzzy Lyapunov–Krasovskii functional method

Adaptive event‐triggered quantized H∞ fuzzy filtering for T‐S fuzzy systems via fuzzy Lyapunov–Krasovskii functional method

Robust Control for Singular Systems Based on the Uncertainty and Disturbance Estimator

Non‐fragile control for dynamic event‐triggered networked systems with randomly occurring nonlinearities

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