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- Title
Adaptive Neural Network Control Scheme of Switched Systems with Input Saturation.
- Authors
Jiang, Xiaoli; Liu, Mingyue; Liu, Siqi; Xu, Jing; Liu, Lina
- Abstract
This paper investigates a scheme of adaptive neural network control for a stochastic switched system with input saturation. The unknown smooth nonlinear functions are approximated directly by neural networks. A modified approach is proposed to deal with unknown functions with nonstrict feedback form in the design process. Furthermore, by combining the auxiliary design signal and the adaptive backstepping design, a valid adaptive neural tracking controller design algorithm is presented such that all the signals of the switched closed-loop system are in probability semiglobally, uniformly, and ultimately bounded, and the tracking error eventually converges to a small neighborhood of the origin in probability. In the end, the effectiveness of the proposed method is verified by a simulation example.
- Subjects
ADAPTIVE fuzzy control; CLOSED loop systems; SMOOTHNESS of functions; STOCHASTIC systems; NONLINEAR functions; ALGORITHMS
- Publication
Discrete Dynamics in Nature & Society, 2020, p1
- ISSN
1026-0226
- Publication type
Article
- DOI
10.1155/2020/7259613