Asynchronous Dissipative Control of Discrete-Time Fuzzy Markov Jump Systems With Dynamic State and Input Quantization

Zhou, Jianping; Dong, Jingjing; Xu, Shengyuan

doi:10.1109/tfuzz.2023.3271348

Cited by 19 publications

(2 citation statements)

References 47 publications

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“…In the study of control systems, most stability analyses of systems are based on Lyapunov stability. In practice, Lyapunov stability can only describe the motion trajectory of the system without constraints on time, and cannot reflect the transient performance of the system 10–12 . However, many phenomena need to be completed within a limited time in real life.…”

Section: Introductionmentioning

confidence: 99%

Finite‐time mixed ℋ∞$$ {\mathscr{H}}_{\infty } $$ and passive filtering for nonlinear singular systems under fading channels

Cai,

Chang

2024

Intl J Robust & Nonlinear

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This article focuses on the finite‐time mixed and passive filtering problem for discrete‐time singular systems with randomly occurring nonlinear perturbations. The main purpose is to design a filter, which ensures the singular error system is stochastically finite‐time bounded and satisfies mixed and passive performance. By constructing an augmented matrix, the properties of matrix determinant and rank are used to prove that the singular system is regular and causal, Finsler's lemma and Projection lemma are used in the design process to acquire additional slack variable matrices, thereby enhancing the solution space with extra degrees of freedom. Then, the unknown parameters of the filter are obtained by solving the less conservative linear matrix inequalities. Finally, the feasibility of the proposed method is verified through a common numerical example and by controlling a DC motor for an inverted pendulum.

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Section: Introductionmentioning

confidence: 99%

Finite‐time mixed ℋ∞$$ {\mathscr{H}}_{\infty } $$ and passive filtering for nonlinear singular systems under fading channels

Cai,

Chang

2024

Intl J Robust & Nonlinear

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“…[15] Due to the limited communication bandwidth and network throughput, the measurement signals are often quantized to mitigate the communication load. [16] Two common types of quantization discussed in the literature on network-based filtering are logarithmic quantization and uniform quantization. In comparison to logarithmic quantization, uniform quantization, which utilizes fixed-point number representation, is considered easier to implement.…”

Section: Introductionmentioning

confidence: 99%

Finite-time ℋ_∞ filtering for Markov jump systems with uniform quantization

Dong 董,

Ma 马,

Zhang 张

et al. 2023

Chinese Phys. B

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This paper is concerned with finite-time H ∞ filtering for Markov jump systems with uniform quantization. The objective is to design quantized mode-dependent filters to ensure that the filtering error system is not only mean-square finite-time bounded but also has a prescribed finite-time H ∞ performance. First, the case where the switching modes of the filter align with those of the MJS is considered. A numerically tractable filter design approach is proposed utilizing a mode-dependent Lyapunov function, Schur’s complement, and Dynkin’s formula. Then, the study is extended to a scenario where the switching modes of the filter can differ from those of the MJS. To address this situation, a mode-mismatched filter design approach is developed by leveraging a hidden Markov model to describe the asynchronous mode switching and the double expectation formula. Finally, a spring system model subject to a Markov chain is employed to validate the effectiveness of the quantized filter design approaches.

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Event-Triggered Control for Roesser Model-Based 2D Markov Jump Systems Under Stochastic Communication Protocol

Zhang,

Ji,

Jiang

et al. 2024

Circuits Syst Signal Process

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Asynchronous Dissipative Control of Discrete-Time Fuzzy Markov Jump Systems With Dynamic State and Input Quantization

Cited by 19 publications

References 47 publications

Finite‐time mixed ℋ∞$$ {\mathscr{H}}_{\infty } $$ and passive filtering for nonlinear singular systems under fading channels

Finite‐time mixed ℋ∞$$ {\mathscr{H}}_{\infty } $$ and passive filtering for nonlinear singular systems under fading channels

Finite-time ℋ_∞ filtering for Markov jump systems with uniform quantization

Event-Triggered Control for Roesser Model-Based 2D Markov Jump Systems Under Stochastic Communication Protocol

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Asynchronous Dissipative Control of Discrete-Time Fuzzy Markov Jump Systems With Dynamic State and Input Quantization

Cited by 19 publications

References 47 publications

Finite‐time mixed ℋ∞$$ {\mathscr{H}}_{\infty } $$ and passive filtering for nonlinear singular systems under fading channels

Finite‐time mixed ℋ∞$$ {\mathscr{H}}_{\infty } $$ and passive filtering for nonlinear singular systems under fading channels

Finite-time ℋ∞ filtering for Markov jump systems with uniform quantization

Event-Triggered Control for Roesser Model-Based 2D Markov Jump Systems Under Stochastic Communication Protocol

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Product

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Finite-time ℋ_∞ filtering for Markov jump systems with uniform quantization