Command filter-based adaptive fault-tolerant tracking control for uncertain non-strict feedback multi-agent systems with or without state constraints

Liu, Zhucheng; Zhang, Tianping; Xia, Meizhen

doi:10.1016/j.jfranklin.2022.09.037

Cited by 5 publications

(2 citation statements)

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“…The desired signal is y d = 0.5 sin(t). In practical systems, the above adaptive ETC scheme also achieves satisfactory tracking results, and all states are within the predetermined bound as illustrated in Figures 9,10…”

Section: F I G U R E 10mentioning

confidence: 78%

“…In Reference 9, an unified method for handling with or without state constraints was proposed by introducing a new constraint function. Reference 10 extended this method to multi‐agent systems. In Reference 11, a new kind of state constraints called function constraints was proposed, which not only included time but also included states from previous moments.…”

Section: Introductionmentioning

confidence: 99%

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Command filter‐based adaptive event‐triggered control for switched nonlinear systems with full state constraints

Zhang,

Feng

2023

Intl J Robust & Nonlinear

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An adaptive event‐triggered control issue based on command filter and dynamic surface control is studied for switched nonlinear systems with full state time‐varying constraints in this article. To handle state constraints, the nonlinear mapping conversion technique is used. Radial basis function neural networks (RBFNNs) are utilized to approximate unknown nonlinear continuous functions. Adaptive control algorithm is designed based on command filtered backstepping technology. Novel even triggered control is constructed for two different cases in the switching interval. Furthermore, all signals in the switched system are proved to be semi‐globally uniformly ultimate bounded (SGUUB) by the aid of dynamic surface control method under arbitrary switching. Meanwhile, all states do not violate the preset constraints and Zeno phenomenon is avoided. The validity of the presented approach is confirmed through a numerical simulation result.

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Section: F I G U R E 10mentioning

confidence: 78%