Tracking control for large‐scale switched nonlinear systems subject to asymmetric input saturation and output hysteresis: A new adaptive network‐based approach

• Published in: International journal of robust and nonlinear control Vol. 32; no. 14; pp. 8052 - 8072
• Main Authors: Han, Yu‐Qun, He, Wen‐Jing, Li, Na, Zhu, Shan‐Liang
• Format: Journal Article
• Language: English
• Published: Bognor Regis Wiley Subscription Services, Inc 25.09.2022
• Subjects: Adaptive control; asymmetric input saturation; Asymmetry; Control methods; Decentralized control; Error functions; Hysteresis models; large‐scale nonlinear systems; Linear functions; multi‐dimensional Taylor network; Neural networks; Nonlinear systems; output hysteresis; Saturation; switched nonlinear systems; Tracking control; Tracking problem
• ISSN: 1049-8923; 1099-1239
• DOI: 10.1002/rnc.6258

For large‐scale switched nonlinear systems subject to asymmetric input saturation and output hysteresis, an adaptive control strategy is put forward by using a novel neural network, that is, multi‐dimensional Taylor network (MTN), which can effectively cope with the output tracking problem of this system. Firstly, asymmetric input saturation is expressed as the combination of a linear function and a bounded error function. Then, the modified Bouc‐Wen hysteresis model is employed to solve the nonlinear problem caused by output hysteresis. Afterwards, based on the approximation ability of MTN, a novel adaptive decentralized control method is designed by combining Lyapunov stability theory with adaptive backstepping technology, which realizes the stability and boundedness of the controlled systems. It should be noted that the asymmetric input saturation, the output hysteresis, large‐scale nonlinear systems and switched nonlinear systems appear in the same framework for the first time. Finally, a practical example and a numerical example are given to verify the availability of the proposed control strategy.