Adaptive decentralized prescribed performance control for a class of large-scale nonlinear systems subject to nonsymmetric input saturations

• Published in: Neural computing & applications Vol. 34; no. 13; pp. 11123 - 11140
• Main Authors: Zhu, Shan-Liang, Han, Yu-Qun
• Format: Journal Article
• Language: English
• Published: London Springer London 01.07.2022; Springer Nature B.V
• Subjects: Adaptive control; Algorithms; Approximation; Artificial Intelligence; Computational Biology/Bioinformatics; Computational Science and Engineering; Computer Science; Control algorithms; Control methods; Control theory; Controllers; Data Mining and Knowledge Discovery; Design; Image Processing and Computer Vision; Nonlinear systems; Original Article; Probability and Statistics in Computer Science; Recursive methods; Saturation; Tracking control; Tracking errors; Multi-dimensional Taylor network; Input saturation; Prescribed performance; Adaptive control; Large-scale nonlinear systems

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...