CLC number: TP273
On-line Access: 2024-08-27
Received: 2023-10-17
Revision Accepted: 2024-05-08
Crosschecked: 2021-06-08
Cited: 0
Clicked: 7144
Citations: Bibtex RefMan EndNote GB/T7714
Xuerao Wang, Qingling Wang, Changyin Sun. Adaptive tracking control of high-order MIMO nonlinear systems with prescribed performance[J]. Frontiers of Information Technology & Electronic Engineering, 2021, 22(7): 986-1001.
@article{title="Adaptive tracking control of high-order MIMO nonlinear systems with prescribed performance",
author="Xuerao Wang, Qingling Wang, Changyin Sun",
journal="Frontiers of Information Technology & Electronic Engineering",
volume="22",
number="7",
pages="986-1001",
year="2021",
publisher="Zhejiang University Press & Springer",
doi="10.1631/FITEE.2000145"
}
%0 Journal Article
%T Adaptive tracking control of high-order MIMO nonlinear systems with prescribed performance
%A Xuerao Wang
%A Qingling Wang
%A Changyin Sun
%J Frontiers of Information Technology & Electronic Engineering
%V 22
%N 7
%P 986-1001
%@ 2095-9184
%D 2021
%I Zhejiang University Press & Springer
%DOI 10.1631/FITEE.2000145
TY - JOUR
T1 - Adaptive tracking control of high-order MIMO nonlinear systems with prescribed performance
A1 - Xuerao Wang
A1 - Qingling Wang
A1 - Changyin Sun
J0 - Frontiers of Information Technology & Electronic Engineering
VL - 22
IS - 7
SP - 986
EP - 1001
%@ 2095-9184
Y1 - 2021
PB - Zhejiang University Press & Springer
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DOI - 10.1631/FITEE.2000145
Abstract: In this paper, an observer-based adaptive prescribed performance tracking control scheme is developed for a class of uncertain multi-input multi-output nonlinear systems with or without input saturation. A novel finite-time neural network disturbance observer is constructed to estimate the system uncertainties and external disturbances. To guarantee the prescribed performance, an error transformation is applied to transfer the time-varying constraints into a constant constraint. Then, by employing a barrier Lyapunov function and the backstepping technique, an observer-based tracking control strategy is presented. It is proven that using the proposed algorithm, all the closed-loop signals are bounded, and the tracking errors satisfy the predefined time-varying performance requirements. Finally, simulation results on a quadrotor system are given to illustrate the effectiveness of the proposed control scheme.
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