Neuroadaptive PI control with prescribed performance for a class of nonaffine systems with non-smooth input saturation
- Resource Type
- Conference
- Authors
- Zhong, Yuanchang; Zhang, Xiaofan; Ma, Tianzhi; Xu, Min
- Source
- 2017 29th Chinese Control And Decision Conference (CCDC) Control And Decision Conference (CCDC), 2017 29th Chinese. :5329-5334 May, 2017
- Subject
- General Topics for Engineers
Power, Energy and Industry Applications
Robotics and Control Systems
Signal Processing and Analysis
Stability analysis
Control design
Convergence
Transient analysis
Artificial neural networks
Neuroadaptive PI controller
Nonaffine systems
Neural networks
Prescribed performance
- Language
- ISSN
- 1948-9447
Based on L 1 adaptive control theory, a novel block backstepping control for a class of uncertain multiple-input-multiple-output nonlinear system is proposed. The matched system parametric uncertainty and unmatched general uncertainty including modeling error and external disturbance are considered in the design. The L 1 adaptive control is integrated with block backstepping to improve the transient performance in addition to stable tracking. The low-pass filter is adopted to guarantee fast adaptive rate without generating high-frequency oscillations in control signal and ensure its smoothness. A reference system is introduced to prove the stability of the closed-loop system via L 1 adaptive theory and Lyapunov theorem. Finally, numeral simulation results show the transient performance and feasibility of the proposed adaptive control. A neuroadaptive PI controller is developed for a class of nonaffine systems with bounded external disturbance and a symmetric non-smooth input saturation. Neural networks's (NNs's) capability of nonlinear function approximation and the use of exponentially decaying and hyperbolic functions in solving prescribed performance (PP) problems. Then, a transformed filtered error is designed to facilitate the control design and analysis. A stability analysis based on Lyapunov method guarantees uniformly ultimate bounded (UUB). Simulations are carried out to verify and clarify the theoretical findings.