Control Synthesis of Hidden Semi-Markov Uncertain Fuzzy Systems via Observations of Hidden Modes

Cai, Bo; Zhang, Lixian; Shi, Yang

doi:10.1109/tcyb.2019.2921811

Cited by 57 publications

(43 citation statements)

References 24 publications

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“…When A d = C qd = 0 or = 0, the nonlinear model (7) becomes the nonlinear system without time delay. It is worth noting that linear systems and many famous chaotic systems with or without time delay, which contain chaotic neural networks, 32 Chua's circuits, 33 and unified chaotic systems, 34 can be converted to model (7).…”

Section: Figurementioning

confidence: 99%

“…Remark 3. Since the controller cannot be fully obtained by the system mode in practice, the conditional probability matrix (10) is used to connect system (7) and controller (9). Then, system (12) can be seen as a double-mode process from (2) and (10).…”

Section: Figurementioning

confidence: 99%

“…Therefore, Markovian jumping systems are studied, which provide the theoretical basis for solving engineering problems . The control for T‐S fuzzy Markovian jump systems was analyzed and researched . Besides, to improve the modeling ability of traditional Markovian jump systems, some questions about semi‐Markovian jump systems were discussed .…”

Section: Introductionmentioning

confidence: 99%

“…[2][3][4][5] The control for T-S fuzzy Markovian jump systems was analyzed and researched. 6,7 Besides, to improve the modeling ability of traditional Markovian jump systems, some questions about semi-Markovian jump systems were discussed. 8,9 These above systems have made great progress on the basis of traditional Markovian jump systems.…”

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confidence: 99%

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Asynchronous control of T‐S fuzzy chaotic systems via a unified model using the hidden Markov model subject to strict dissipativity

Tong

Chen

et al. 2019

Optim Control Appl Methods

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Summary The asynchronous control for the unified model of chaotic systems with Markovian jumping parameters is considered via the Takagi‐Sugeno (T‐S) fuzzy approach in this paper. According to jumping modes for chaotic systems and modes for the asynchronous controller, a double‐mode process is generated. By introducing the hidden Markov model (HMM), the asynchronization phenomenon is represented between the controller and chaotic systems. By linear matrix inequalities (LMIs), some conditions are received to guarantee the stochastic stability and the strict dissipativity for chaotic systems. Based on the stochastic stability theory and the dissipativity theory, the asynchronous controller is discussed. The proposed method can be applied to the mode‐independent controller and the synchronous controller. Finally, the effectiveness of the proposed controller is illustrated by two examples.

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Section: Figurementioning

confidence: 99%

Section: Figurementioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

mentioning

confidence: 99%

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Asynchronous control of T‐S fuzzy chaotic systems via a unified model using the hidden Markov model subject to strict dissipativity

Tong

Chen

et al. 2019

Optim Control Appl Methods

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“…In the existing results, the switching laws are generally divided into two categories, one is nondeterministic switching signals including dwell‐time switching, average dwell‐time switching, and persistent dwell‐time switching; the other is stochastic switching signals, such as hidden semi‐Markov switching and stochastic switching. The works in References 24‐26 investigated semi‐Markov jump systems with nondeterministic switching signals and stochastic switching signals, respectively. Recently, some important backstepping control approaches have been developed for several classes of switched nonlinear systems under arbitrary switching laws 27,28 .…”

Section: Introductionmentioning

confidence: 99%

Adaptive fuzzy finite‐time optimal control for switched nonlinear systems

Fan

2020

Optim Control Appl Methods

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Summary This article addresses the adaptive fuzzy finite‐time control problem for a class of switched nonlinear systems whose powers are positive odd rational numbers and vary with the switching signal. The fuzzy logic systems (FLSs) are used to approximate the unknown nonlinearities of the controlled systems, and then by combining backstepping control algorithm with adding a power integrator technique, an adaptive finite‐time controller is designed. By modifying and optimizing the relevant design parameters of the proposed adaptive finite‐time controller, a novel adaptive finite‐time optimal control approach is developed. The proposed two adaptive finite‐time optimal control schemes can guarantee semi‐globally practically finite‐time stability of the closed‐loop system. Moreover, the adaptive finite‐time optimal controller can also achieve optimized performance in relation to the cost functional. Finally, a simulation example is given to illustrate the effectiveness of the proposed two adaptive finite‐time control strategies.

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Dynamic event‐triggered asynchronous security load frequency control for semi‐Markov jump multi‐area power systems against deception attacks

Li,

Cheng

et al. 2023

Adaptive Control & Signal

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This paper focuses on the issue of dynamic event‐triggered (DET) asynchronous security load frequency control (LFC) for uncertain semi‐Markov jump interconnected multi‐area power systems (IMAPSs). Initially, the semi‐Markov process which in the presence of partially unknown transition rates (TRs) is exactly introduced to model the switching behaviors of the IMAPSs. Subsequently, the DET mechanism is scheduled to alleviate the transmission frequency and guarantee the desired control performance. Furthermore, the probabilistic deception attacks are taken into consideration, which is much more apt for the practical engineering background. Additionally, a hidden Markov model (HMM) is borrowed to depict the modes asynchronous phenomenon between the security controller and the semi‐Markov jump IMAPSs. Afterwards, on the basis of Lyapunov‐Krasovskii functional method and stochastic analysis technique, sufficient conditions with two cases are derived in the form of linear matrix inequalities (LMIs) to guarantee the stochastic stability with an performance of the semi‐Markov jump IMAPSs. Ultimately, a numerical example is exhibited to verify the solvability and practicability of the proposed control strategy.

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Control Synthesis of Hidden Semi-Markov Uncertain Fuzzy Systems via Observations of Hidden Modes

Cited by 57 publications

References 24 publications

Asynchronous control of T‐S fuzzy chaotic systems via a unified model using the hidden Markov model subject to strict dissipativity

Asynchronous control of T‐S fuzzy chaotic systems via a unified model using the hidden Markov model subject to strict dissipativity

Adaptive fuzzy finite‐time optimal control for switched nonlinear systems

Dynamic event‐triggered asynchronous security load frequency control for semi‐Markov jump multi‐area power systems against deception attacks

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