Hybrid threshold strategy‐based adaptive tracking control for nonlinear stochastic systems with full‐state constraints

2020 ◽  
Vol 30 (15) ◽  
pp. 6189-6206
Author(s):  
Changchun Hua ◽  
Rui Meng ◽  
Kuo Li
Keyword(s):  
Tracking Control ◽  
State Constraints ◽  
Stochastic Systems ◽  
Threshold Strategy ◽  
Nonlinear Stochastic Systems ◽  
Adaptive Tracking Control ◽  
Adaptive Tracking ◽  
Full State ◽  
Full State Constraints

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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