Adaptive multi‐dimensional Taylor network tracking control for nonlinear systems with input saturation and full state time‐varying constraints

• Published in: International journal of adaptive control and signal processing Vol. 36; no. 9; pp. 2152 - 2166
• Main Authors: Han, Yu‐Qun, Liu, Si‐Min, Du, Yang, Yang, Shu‐Guo
• Format: Journal Article
• Language: English
• Published: Bognor Regis Wiley Subscription Services, Inc 01.09.2022
• Subjects: Adaptive control; Control methods; full state constraints; input saturation; Liapunov functions; multi‐dimensional Taylor network; Nonlinear control; Nonlinear systems; Saturation; Tracking control
• ISSN: 0890-6327; 1099-1115
• DOI: 10.1002/acs.3447

Summary In this article, an adaptive multi‐dimensional Taylor network (MTN) control approach is developed for nonlinear systems subject to input saturation and full state time‐varying constraints. Using the function approximation property of MTN, an adaptive tracking control method is developed by incorporating the concept of time‐varying state constraints into the construct of barrier Lyapunov functions. The proposed approach not only ensures all closed‐loop system signals are bounded but also that all states of the system never violate the given time‐varying constraints. The most important advantage of the proposed control strategy is that it can obtain satisfactory control effects with low computational cost. Finally, two examples are given to validate the effectiveness of the proposed method.