Estimation for Fuzzy Semi-Markov Jump Systems With Indirectly Accessible Mode Information and Nonideal Data Transmission

Cai, Bo; Yang, Jianan; Yuan, Shuai; Shi, Yang; Zhang, Lixian

doi:10.1109/tsmc.2019.2929966

Cited by 33 publications

(13 citation statements)

References 31 publications

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“…Remark 9. Considering that the derivatives ( ḋ(t) and ḋ1 (t)) of time delays are not continuous, the Lyapunov function is constructed as (20). It can be noted that the Lyapunov function is decreasing at the discontinuities of d(t) and d 1 (t).…”

Section: Stochastic Stability Analysismentioning

confidence: 99%

“…Considering the observed mode information, the state estimation and stabilization of hidden discrete-time linear SMJSs have been discussed with observed mode-dependent filter and emission probability approach. 17 For more complex nonlinear SMJSs, the robust control method, 18 T-S fuzzy control approach, [19][20][21] sliding mode control strategy, 8 adaptive control process, 9 and neural network algorithm 22 can be applied to deal with the nonlinearity. For the repeated scalar nonlinearity whose upper bound of nonlinear function is known, the robust controller for discrete-time nonlinear singularly perturbed SMJSs is designed and the H ∞ performance is analyzed.…”

Section: Introductionmentioning

confidence: 99%

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Adaptive event‐triggered resilient stabilization for nonlinear semi‐Markov jump systems subject to DoS attacks

Lü

Xia

et al. 2022

Intl J Robust & Nonlinear

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This article investigates the problem of adaptive event‐triggered resilient stabilization for nonlinear semi‐Markov jump systems with DoS attacks. In this article, both DoS attacks and event‐triggered transmission strategy (ETTS) are considered. The DoS attacks may disturb the event‐triggered strategy, which implies that the original inequality condition of ETTS will no longer be satisfied. Different from the traditional ETTS, the adaptive ETTS is designed to reduce bandwidth usage. Based on the adaptive ETTS and resilient controller, the sufficient condition for stochastic stability of the closed‐loop system is proposed. Then, the calculation method of controller and observer parameters is given in the form of linear matrix inequality. Finally, the proposed adaptive event‐triggered resilient controller is applied to a single‐link robot arm model, which can show effectiveness of the proposed method.

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Section: Stochastic Stability Analysismentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Adaptive event‐triggered resilient stabilization for nonlinear semi‐Markov jump systems subject to DoS attacks

Lü

Xia

et al. 2022

Intl J Robust & Nonlinear

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“…where 𝛼 v > 0 denotes the chosen update rate and z(k + 1) is obtained from z(k + 1) = F s (z(k), q d (𝜇 i (l(z(k), s)))) with s being decided by (17). Define the actor network as…”

Section: Neural Network Implementationmentioning

confidence: 99%

“…With the developments of networked control systems, 17 more and more attention has been paid to the utilization efficiency of network resources. For this reason, the quantization control and event‐based sampling and transmission have been used widely 18‐22 .…”

Section: Introductionmentioning

confidence: 99%

Quantized optimal output feedback control and optimal triggering signal co‐design for unknown discrete‐time nonlinear systems

Han

Hao

et al. 2022

Optim Control Appl Methods

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A problem of optimizing the cost function incorporated into the transmission cost is proposed for completely unknown discrete-time systems in this article. At first, a switched system containing two modes is formulated based on whether the triggering is executed or not, and the corresponding cost function and output feedback control law are also derived. By giving the formulated switched system, the triggering signal turns into the switching signal and the proposed problem is converted into an optimal control problem for the formulated discrete-time switched system. Secondly, a model network is presented to approximate the system dynamic since the dynamic model is completely unknown. Thirdly, in view of ADP-based optimal control methods of switched systems, critic and actor networks are applied respectively to approximate the optimal cost function and the optimal output feedback control law, and a PI-based online learning method is proposed. When weights of critic and actor networks are obtained and implemented through the proposed online learning method, the optimal triggering signal is derived. Fourthly, the convergent property is given to guarantee the obtained results are optimal. At last, the validity of the proposed method is shown by simulation results of two examples.

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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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Estimation for Fuzzy Semi-Markov Jump Systems With Indirectly Accessible Mode Information and Nonideal Data Transmission

Cited by 33 publications

References 31 publications

Adaptive event‐triggered resilient stabilization for nonlinear semi‐Markov jump systems subject to DoS attacks

Adaptive event‐triggered resilient stabilization for nonlinear semi‐Markov jump systems subject to DoS attacks

Quantized optimal output feedback control and optimal triggering signal co‐design for unknown discrete‐time nonlinear systems

Adaptive fuzzy finite‐time optimal control for switched nonlinear systems

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