Distributed Sliding-Mode Tracking Control of Second-Order Nonlinear Multiagent Systems: An Event-Triggered Approach

This paper investigates the non-fragile H∞ synchronization issue for a class of discrete-time T-S fuzzy Markov jump systems. With regard to the T-S fuzzy model, a novel processing method based on matrix transformation is introduced to deal with the double summation inequality containing fuzzy weighting functions, which may be beneficial to obtain conditions with less conservatism. In view of the fact that the uncertainties may occur randomly in the execution of actuator, a non-fragile controller design scheme is presented by virtue of the Bernoulli distributed white sequence. The main novelty of this paper lies in that the transition probabilities of Markov chain are considered to be piecewise time-varying, and whose variation characteristics are described by the persistent dwell-time switching regularity. Then, based on Lyapunov stability theory, it is concluded that the resulting synchronization error system is mean-square exponentially stable with a prescribed H∞ performance in the presence of actuator gain variations. Finally, an illustrative example about Lorenz chaotic systems is provided to show the effectiveness of the established results. Index Terms-T-S fuzzy Markov jump chaotic systems, persistent dwell-time switching, mean-square exponential stability, non-fragile H∞ synchronization.

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“…Apparently, one can get Ω(k fs , k fs+1 ) ≤ T (s) + 1. Then, combining with (19) and (22), one can deduce…”

Section: A Stabilization and Performance Analysismentioning

confidence: 99%

“…Considering k ∈ [k fs , k fs+1 ), s ∈ Z ≥1 , it can be inferred from Ω(l, k) < ( k−l τ P +T P + 1)(T P + 1), (22) and (23) that E {V (e(k),…”

Section: A Stabilization and Performance Analysismentioning

confidence: 99%

$\mathcal {H}_{\infty }$ Synchronization for Fuzzy Markov Jump Chaotic Systems With Piecewise-Constant Transition Probabilities Subject to PDT Switching Rule

Wang

Xia

Shen

et al. 2021

IEEE Trans. Fuzzy Syst.

254

105

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“…Over the past decades, control problem has attracted respectable attention 1‐16 . The effect of the constraints exists in many practical control systems, such as physical stoppages and chemical reactor temperature.…”

Section: Introductionmentioning

confidence: 99%

Adaptive fuzzy finite‐time fault‐tolerant control of nonlinear systems with state constraints and input quantization

Pan

Yang

et al. 2020

Adaptive Control & Signal

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Summary This article concentrates on an adaptive finite‐time fault‐tolerant fuzzy tracking control problem for nonstrict feedback nonlinear systems with input quantization and full‐state constraints. By utilizing the fuzzy logic systems and less adjustable parameters method, the unknown nonlinear functions are addressed in each step process. In addition, a dynamic surface control technique combined with fuzzy control is introduced to tackle the variable separation problem. The problem for the effect of quantization and unlimited number of actuator faults is tackled by a damping term with smooth function in the intermediate control law. Finite‐time stability is achieved by combining barrier Lyapunov functions and backstepping method. The finite‐time controller is designed such that all the responses of the systems are semiglobal practical finite‐time stable and ensured to remain in the predefined compact sets while tracking error converges to a small neighborhood of the origin in finite time. Finally, simulation examples are utilized to testify the validity of the investigated strategy.

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“…13,14 One of the basic research directions of distributed cooperative control is consensus, which means that the agents can reach an agreement with respect to a certain number of interested variables by interacting with their local neighbors. [15][16][17][18][19][20][21] The consensus can be categorized into leader-follower and leaderless, depending on whether there is a leader or not. The former has been widely investigated from different perspectives.…”

Section: Introductionmentioning

confidence: 99%

Adaptive neural control for multiagent systems with asymmetric time‐varying state constraints and input saturation

Yang

Xiao

Yin

et al. 2020

Intl J Robust & Nonlinear

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This article investigates the leader-follower consensus problem of a class of non-strict-feedback nonlinear multiagent systems with asymmetric time-varying state constraints (ATVSC) and input saturation, and an adaptive neural control scheme is developed. By introducing the distributed sliding-mode estimator, each follower can obtain the estimation of leader's trajectory and track it directly. Then, with the help of time-varying asymmetric barrier Lyapunov function and radial basis function neural networks, the controller is designed based on backstepping technique. Furthermore, the mean-value theorem and Nussbaum function are utilized to address the problems of input saturation and unknown control direction. Moreover, the number of adaptive laws is equal to that of the followers, which reduces the computational complexity. It is proved that the leader-follower consensus tracking control is achieved without violating the ATVSC, and all closed-loop signals are semiglobally uniformly ultimately bounded. Finally, the simulation results are provided to verify the effectiveness of the control scheme.

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Distributed Sliding-Mode Tracking Control of Second-Order Nonlinear Multiagent Systems: An Event-Triggered Approach

Cited by 200 publications

References 57 publications

$\mathcal {H}_{\infty }$ Synchronization for Fuzzy Markov Jump Chaotic Systems With Piecewise-Constant Transition Probabilities Subject to PDT Switching Rule

$\mathcal {H}_{\infty }$ Synchronization for Fuzzy Markov Jump Chaotic Systems With Piecewise-Constant Transition Probabilities Subject to PDT Switching Rule

Adaptive fuzzy finite‐time fault‐tolerant control of nonlinear systems with state constraints and input quantization

Adaptive neural control for multiagent systems with asymmetric time‐varying state constraints and input saturation

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