Removing Feasibility Conditions on Adaptive Neural Tracking Control of Nonlinear Time-Delay Systems With Time-Varying Powers, Input, and Full-State Constraints

2020 ◽  
pp. 1-12
Author(s):  
Chao Guo ◽  
Xue-Jun Xie ◽  
Zeng-Guang Hou
Keyword(s):  
Time Delay ◽  
Tracking Control ◽  
State Constraints ◽  
Delay Systems ◽  
Time Varying ◽  
Time Delay Systems ◽  
Full State ◽  
Full State Constraints

Command filtered adaptive neural tracking control of uncertain nonlinear time-delay systems with asymmetric time-varying full state constraints and actuator saturation

2020 ◽  
pp. 095965182097526
Author(s):  
Yuxiang Wu ◽  
Tian Xu ◽  
Haoran Fang
Keyword(s):  
Time Delay ◽  
Tracking Control ◽  
State Constraints ◽  
Actuator Saturation ◽  
Small Neighborhood ◽  
Delay Systems ◽  
Time Varying ◽  
Time Delay Systems ◽  
Full State ◽  
Full State Constraints

This article investigates the command filtered adaptive neural tracking control for uncertain nonlinear time-delay systems subject to asymmetric time-varying full state constraints and actuator saturation. To stabilize such a class of systems, the radial basis function neural networks and the backstepping technique are used to structure an adaptive controller. The command filter is utilized to overcome the complexity explosion problem in backstepping. By employing the Lyapunov–Krasovskii functionals, the effect of time-delay is eliminated. The asymmetric time-varying barrier Lyapunov functions are designed to ensure full state constraint satisfaction. Moreover, the hyperbolic tangent function and an instrumental variable are introduced to deal with actuator saturation. All signals in the closed-loop system are proved to be bounded and the tracking error converges to a small neighborhood of the origin. Finally, two examples are provided to illustrate the effectiveness of the proposed method.

Adaptive tracking control for nonlinear time-delay systems with time-varying full state constraints

2020 ◽  
Vol 42 (12) ◽  
pp. 2178-2190
Author(s):  
Yuxiang Wu ◽  
Tian Xu ◽  
Hongqiang Mo
Keyword(s):  
Time Delay ◽  
Tracking Control ◽  
State Constraints ◽  
Delay Systems ◽  
Time Varying ◽  
Feedback Systems ◽  
Adaptive Tracking Control ◽  
Adaptive Tracking ◽  
Full State ◽  
Full State Constraints

This paper presents an adaptive tracking control approach for a class of uncertain nonlinear strict-feedback systems subject to time-varying full state constraints and time-delays. To stabilize such systems, an adaptive tracking controller is structured by combining the neural networks and the backstepping technique. To guarantee all states do not violate the time-varying constraint sets, the appropriate time-varying Barrier Lyapunov functions are employed at each stage of the backstepping procedure. By using the Lyapunov-Krasovskii functionals, the effect of time delay is eliminated. It is proved that the output follows the desired signal well without violating any constraints, and all the signals in the closed-loop system are semiglobal uniformly ultimately bounded by using the Lyapunov analysis. Finally, a comparison study simulation is provided to illustrate the effectiveness of the proposed control strategy.

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