Adaptive neural tracking control for nonlinear switched systems with dynamic uncertainties
- Resource Type
- Conference
- Authors
- Zhou, Wanlu; Li, Huan; Niu, Ben
- Source
- 2018 Chinese Control And Decision Conference (CCDC) Chinese Control And Decision Conference (CCDC), 2018. :3932-3937 Jun, 2018
- Subject
- General Topics for Engineers
Power, Energy and Industry Applications
Robotics and Control Systems
Signal Processing and Analysis
Switches
Adaptive systems
Nonlinear dynamical systems
Switched systems
Neural networks
Adaptive tracking control
backstepping approach
nonlinear switched system
neural networks
- Language
- ISSN
- 1948-9447
This paper investigates the problem of adaptive approximation-based neural tracking control strategy for a class of switched non-lower triangular nonlinear systems with dynamic uncertainties. The design hardships, which exist in unmodeled dynamics and non-lower triangular form, are tackled by utilizing a dynamic signal and a variable partition strategy for the nonlinear functions with all state variables, respectively. The obtained result shows that all signals of the closed-loop switched system are semi-global bounded with the designed controller and the system output can be guaranteed to enter a small region around the origin.