Adaptive Event-Triggered Finite-Time Dissipative Filtering for Interval Type-2 Fuzzy Markov Jump Systems With Asynchronous Modes

Liu, Jian; Ran, Guangtao; Huang, Yiqing; Han, Chunsong; Yao, Yu; Sun, Changyin

doi:10.1109/tcyb.2021.3053627

Cited by 69 publications

(25 citation statements)

References 56 publications

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“…23,24 Therefore, finite-time boundedness analysis of systems has attracted constant research interest. 25,26 For instance, in Reference 27, the finite-time control problem was studied for switched nonlinear time-delayed systems; the issue of finite-time l 2 -l ∞ non-fragile state estimation was addressed in Reference 28 for neural MJSs with unreliable communication links; the finite-time filtering was concerned for MJSs with time-varying transition probabilities in Reference 29. Furthermore, it is now recognized that the asynchronous phenomenon is widespread in practice between the modes of the filter and the modes of the original system.…”

Section: Tmentioning

confidence: 99%

“…Different from the traditional Lyapunov stability, finite‐time boundedness is focused on the transient performance of a system, and it is more important in many practical systems, as communication networks, aircraft control systems and so forth 23,24 . Therefore, finite‐time boundedness analysis of systems has attracted constant research interest 25,26 . For instance, in Reference 27, the finite‐time control problem was studied for switched nonlinear time‐delayed systems; the issue of finite‐time

l_{2}

‐

l_{\infty}

non‐fragile state estimation was addressed in Reference 28 for neural MJSs with unreliable communication links; the finite‐time filtering was concerned for MJSs with time‐varying transition probabilities in Reference 29.…”

Section: Introductionmentioning

confidence: 99%

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Finite‐time asynchronous dissipative filtering for Markovian jump systems with time‐varying delays and randomly occurred nonlinearity

Wang

Guo

2022

Adaptive Control & Signal

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Summary The finite‐time dissipative filtering problem for time‐varying delayed Markovian jump systems with randomly occurred nonlinearity is addressed in this article. The modes of the desired filter are supposed to be asynchronous with the modes of the original system, which is more in line with the practical situation. The purpose of the problem under investigation is an asynchronous filter design which could make the error system finite‐time bounded as well as strictly dissipative. By constructing novel Lyapunov–Krasovskii functionals that covers the aforementioned two asynchronous modes and utilizing the theory of finite‐time analysis, some sufficient conditions are put forward to obtain the desired asynchronous filter by virtue of the linear matrix inequalities approach. A numerical example and a tunnel diode circuit are finally provided to demonstrate the effectiveness of our proposed method.

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Section: Tmentioning

confidence: 99%

l_{2}

‐

l_{\infty}

Section: Introductionmentioning

confidence: 99%

Finite‐time asynchronous dissipative filtering for Markovian jump systems with time‐varying delays and randomly occurred nonlinearity

Wang

Guo

2022

Adaptive Control & Signal

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“…In the Ref. [29], the L ∞ scheme was developed for fuzzy MJSs, and the effect of transmission delay was studied. In the Refs.…”

Section: Literature Reviewmentioning

confidence: 99%

Automatic Control for Time Delay Markov Jump Systems under Polytopic Uncertainties

et al. 2022

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The Markov jump systems (MJSs) are a special case of parametric switching system. However, we know that time delay inevitably exists in many practical systems, and is known as the main source of efficiency reduction, and even instability. In this paper, the stochastic stable control design is discussed for time delay MJSs. In this regard, first, the problem of modeling of MJSs and their stability analysis using Lyapunov-Krasovsky functions is studied. Then, a state-feedback controller (SFC) is designed and its stability is proved on the basis of the Lyapunov theorem and linear matrix inequalities (LMIs), in the presence of polytopic uncertainties and time delays. Finally, by various simulations, the accuracy and efficiency of the proposed methods for robust stabilization of MJSs are demonstrated.

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“…To overcome this drawback, the event-triggered control scheme is proposed to manage the information data release only when the given condition is triggered, in other words, only necessary data will be transmitted [10]. The event-triggered control problem of finite dimensional systems were studied widely [11][12][13][14][15][16][34][35][36][37], while Yao et al [17] recently investigated event-triggered control problem for DPSs as the first attempt. Based on mobile sensor and actuator, Jiang et al [18] considered event-driven observer-based control problem for DPSs by employing operator semigroup method.…”

Section: Introductionmentioning

confidence: 99%

“…Therefore, it is necessary to develop an adaptive event-triggered law to adapt such changing condition. Recently, Ran et al [36] and Liu et al [37] proposed event-triggered communication scheme to analyze problems of both dissipative control and finite-time filtering of interval type-2 fuzzy systems, respectively. However, there are few references published on adaptive event-triggered control for DPSs with Markov jump parameters.…”

Section: Introductionmentioning

confidence: 99%

Sampled-Data Control of Distributed Parameter Systems via an Event-Based Communication Scheme

Zhu

2021

IEEE Access

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This paper studies the problem of event-triggered control for a class of networked distributed parameter systems with Markov jump parameters. To reduce the number of packages transmitted over the communication network, an adaptive event-triggered mechanism is introduced. The Galerkin method is employed to obtain the nonlinear ordinary differential equation systems, which can accurately describe the dynamics of the dominant modes of the considered distributed parameter systems. The systems are subsequently parameterized by a multilayer neural network with one-hidden layer and zero bias terms, and the linear ordinary differential equation systems are derived. Then, Lyapunov approach is used to analyze stability of the considered systems, and by employing the strong law of large numbers and Gronwall inequality technique, almost surely exponential stability condition is derived. Moreover, a linear sampleddata-based controller is designed to stabilize the closed-loop systems. Finally, a practical example is shown to demonstrate the effectiveness of the achieved theoretical results.INDEX TERMS Distributed parameter systems, Markov jump parameters, Galerkin method, neural model, adaptive event-triggered networked control, almost surely exponential stability.

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Adaptive Event-Triggered Finite-Time Dissipative Filtering for Interval Type-2 Fuzzy Markov Jump Systems With Asynchronous Modes

Cited by 69 publications

References 56 publications

Finite‐time asynchronous dissipative filtering for Markovian jump systems with time‐varying delays and randomly occurred nonlinearity

Finite‐time asynchronous dissipative filtering for Markovian jump systems with time‐varying delays and randomly occurred nonlinearity

Automatic Control for Time Delay Markov Jump Systems under Polytopic Uncertainties

Sampled-Data Control of Distributed Parameter Systems via an Event-Based Communication Scheme

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