A simplified adaptive tracking control for nonlinear pure‐feedback systems with input delay and full‐state constraints

• Published in: International journal of adaptive control and signal processing Vol. 35; no. 12; pp. 2521 - 2536
• Main Authors: Wang, Nan, Fu, Zhumu, Tao, Fazhan, Song, Shuzhong, Wang, Tong
• Format: Journal Article
• Language: English
• Published: Bognor Regis Wiley Subscription Services, Inc 01.12.2021
• Subjects: adaptive backstepping control; Adaptive control; Delay; Differential calculus; dynamic surface control; Feedback; full‐state constraints; Liapunov functions; Neural networks; Nonlinear control; Nonlinear systems; Pade approximation; pure‐feedback systems; Radial basis function; radial basis function neural networks; Tracking control
• ISSN: 0890-6327; 1099-1115
• DOI: 10.1002/acs.3335

Summary This article investigated the adaptive backstepping tracking control for a class of pure‐feedback systems with input delay and full‐state constraints. With the help of mean value theorem, the system is transformed into strict‐feedback one. By introducing the Pade approximation method, the effect of input delay was compensated. Radial basis function neural networks are utilized to approximate the unknown nonlinear functions. Furthermore, in order to reduce the computational burden by introducing backstepping design technique, dynamic surface control technique was employed. In addition, the number of the adaptive parameters that should be updated online was also reduced. By utilizing the barrier Lyapunov function, the closed‐loop nonlinear system is guaranteed to be semi‐globally ultimately uniformly bounded. Finally, a numerical simulation example is given to show the effectiveness of the proposed control strategy.