Adaptive tracking control for a class of uncertain pure-feedback systems

2015 ◽  
Vol 26 (5) ◽  
pp. 1143-1154 ◽  
Author(s):  
Yong-Hua Liu
Keyword(s):  
Tracking Control ◽  
Feedback Systems ◽  
Adaptive Tracking Control ◽  
Adaptive Tracking

Adaptive tracking control for uncertain switched stochastic nonlinear pure-feedback systems with unknown backlash-like hysteresis

2017 ◽  
Vol 354 (4) ◽  
pp. 1801-1818 ◽  
Author(s):  
Guozeng Cui ◽  
Shengyuan Xu ◽  
Baoyong Zhang ◽  
Junwei Lu ◽  
Ze Li ◽  
...  
Keyword(s):  
Tracking Control ◽  
Feedback Systems ◽  
Adaptive Tracking Control ◽  
Adaptive Tracking

scholarly journals Approximation-Based Fixed-Time Adaptive Tracking Control for a Class of Uncertain Nonlinear Pure-Feedback Systems

Complexity ◽  
2020 ◽  
Vol 2020 ◽  
pp. 1-17
Author(s):  
Cheng He ◽  
Jian Wu ◽  
Jiyang Dai ◽  
Zhe Zhang ◽  
Libin Xu ◽  
...  
Keyword(s):  
Tracking Control ◽  
Tracking Error ◽  
Fixed Time ◽  
Mean Value ◽  
Design Parameters ◽  
Mean Value Theorem ◽  
Feedback Systems ◽  
Adaptive Tracking Control ◽  
Adaptive Tracking ◽  
Time Control

This paper examines approximation-based fixed-time adaptive tracking control for a class of uncertain nonlinear pure-feedback systems. Novel virtual and actual controllers are designed that resolve the meaninglessness of virtual and actual controllers at the origin and in the negative domain, and the sufficient condition for the system to have semiglobal fixed-time stability is also provided. Radial basis function neural networks are introduced to approximate unknown functions for solving the fixed-time control problem of unknown nonlinear pure-feedback systems, and the mean value theorem is used to solve the problem of nonaffine structure in nonlinear pure-feedback systems. The controllers designed in this paper ensure that all signals in the closed-loop system are semiglobally uniform and ultimately bounded in a fixed time. Two simulation results show that appropriate design parameters can limit the tracking error within a region of the origin in a fixed time.

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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