Adaptive practical fixed‐time tracking control for uncertain non‐strict‐feedback systems with input delay and prescribed boundary constraints

2021 ◽  
Author(s):  
Xu Zhang ◽  
Jieqing Tan ◽  
Yangang Yao ◽  
Jian Wu
Keyword(s):  
Tracking Control ◽  
Fixed Time ◽  
Input Delay ◽  
Feedback Systems ◽  
Boundary Constraints ◽  
Strict Feedback

Adaptive Fuzzy Backstepping Tracking Control for Strict-Feedback Systems With Input Delay

2017 ◽  
Vol 25 (3) ◽  
pp. 642-652 ◽  
Author(s):  
Hongyi Li ◽  
Lijie Wang ◽  
Haiping Du ◽  
Abdesselem Boulkroune
Keyword(s):  
Tracking Control ◽  
Input Delay ◽  
Feedback Systems ◽  
Adaptive Fuzzy ◽  
Strict Feedback

scholarly journals Dynamic Event-Triggered Adaptive Tracking Control for a Class of Unknown Stochastic Nonlinear Strict-Feedback Systems

Symmetry ◽  
2021 ◽  
Vol 13 (9) ◽  
pp. 1648
Author(s):  
Yingying Fu ◽  
Jing Li ◽  
Shuiyan Wu ◽  
Xiaobo Li
Keyword(s):  
Tracking Control ◽  
Stochastic Nonlinear Systems ◽  
Fourth Moment ◽  
Feedback Systems ◽  
Nonlinear Functions ◽  
Feedback Form ◽  
Adaptive Tracking Control ◽  
Dynamic Event ◽  
Event Triggered ◽  
Strict Feedback

In this paper, the dynamic event-triggered tracking control issue is studied for a class of unknown stochastic nonlinear systems with strict-feedback form. At first, neural networks (NNs) are used to approximate the unknown nonlinear functions. Then, a dynamic event-triggered controller (DETC) is designed through the adaptive backstepping method. Especially, the triggered threshold is dynamically adjusted. Compared with its corresponding static event-triggered mechanism (SETM), the dynamic event-triggered mechanism (DETM) can generate a larger execution interval and further save resources. Moreover, it is verified by two simulation examples that show that the closed-loop stochastic system signals are ultimately fourth moment semi-globally uniformly bounded (SGUUB).

scholarly journals Distributed Adaptive Fixed-Time Tracking Consensus Control for Multiple Uncertain Nonlinear Strict-Feedback Systems under a Directed Graph

Complexity ◽  
2020 ◽  
Vol 2020 ◽  
pp. 1-21
Author(s):  
Pinwei Li ◽  
Jiyang Dai ◽  
Jin Ying ◽  
Zhe Zhang ◽  
Cheng He
Keyword(s):  
Directed Graph ◽  
Control Strategy ◽  
Design Procedure ◽  
Fixed Time ◽  
Convergence Time ◽  
Approximation Technique ◽  
Feedback Systems ◽  
Consensus Control ◽  
Consensus Tracking ◽  
Strict Feedback

In this brief, we study the distributed adaptive fixed-time tracking consensus control problem for multiple strict-feedback systems with uncertain nonlinearities under a directed graph topology. It is assumed that the leader’s output is time varying and has been accessed by only a small fraction of followers in a group. The distributed fixed-time tracking consensus control is proposed to design local consensus controllers in order to guarantee the consensus tracking between the followers and the leader and ensure the error convergence time is independent of the systems’ initial state. The function approximation technique using radial basis function neural networks (RBFNNs) is employed to compensate for unknown nonlinear terms induced from the controller design procedure. From the Lyapunov stability theorem and graph theory, it is shown that, by using the proposed fixed-time control strategy, all signals in the closed-loop system and the consensus tracking errors are cooperatively semiglobally uniformly bounded and the errors converge to a neighborhood of the origin within a fixed time. Finally, the effectiveness of the proposed control strategy has been proved by rigorous stability analysis and two simulation examples.

Command filtered backstepping tracking control of uncertain nonlinear strict-feedback systems under a directed graph

2016 ◽  
Vol 39 (7) ◽  
pp. 1027-1036 ◽  
Author(s):  
Yi Zhang ◽  
Guozeng Cui ◽  
Guangming Zhuang ◽  
Junwei Lu ◽  
Ze Li
Keyword(s):  
Directed Graph ◽  
Tracking Control ◽  
Design Procedure ◽  
Design Parameters ◽  
Feedback Systems ◽  
Consensus Tracking ◽  
Backstepping Approach ◽  
Non Linear ◽  
Distributed Controllers ◽  
Strict Feedback

This paper studies the distributed consensus tracking control problem of multiple uncertain non-linear strict-feedback systems under a directed graph. The command filtered backstepping approach is utilised to alleviate computation burdens and construct distributed controllers, which involves compensated signals eliminating filtered error effects in the design procedure. Neural networks are employed to estimate uncertain non-linear items. Using a Lyapunov stability theorem, it is proved that all signals in the closed-looped systems are semi-globally uniformly ultimately bounded. In addition, consensus errors converge to a small neighbourhood of the origin by adjusting the appropriate design parameters. Finally, simulation results are presented to demonstrate the effectiveness of the developed control design approach.

Sign in / Sign up

Export Citation Format

Share Document