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- Title
Adaptive decentralized prescribed performance control for a class of large-scale nonlinear systems subject to nonsymmetric input saturations.
- Authors
Zhu, Shan-Liang; Han, Yu-Qun
- Abstract
This paper investigates an adaptive decentralized predefined performance control problem for a class of large-scale nonlinear systems with nonsymmetric input saturation by using multi-dimensional taylor network (MTN) approach. Firstly, the input saturation model is approximated by a smooth function with a bounded approximation error and unknown nonlinear functions are estimated by MTNs. Secondly, a decentralized tracking control algorithm is established by integrating the idea of prescribed performance control into backstepping recursive technique. Thirdly, by using the designed MTN-based adaptive decentralized controller, all the closed-loop signals are bounded and all the tracking errors satisfy the predefined transient and steady-state performance, respectively. Finally, the presented control method is effective by introducing three examples, and the simulation results verify that the correctness and reasonableness of the proposed control algorithm.
- Subjects
NONLINEAR systems; LARGE scale systems; SMOOTHNESS of functions; APPROXIMATION error; NONLINEAR functions; ADAPTIVE control systems; TRACKING algorithms
- Publication
Neural Computing & Applications, 2022, Vol 34, Issue 13, p11123
- ISSN
0941-0643
- Publication type
Article
- DOI
10.1007/s00521-022-07032-8