Finite-Time Tracking Control for Nonlinear Systems via Adaptive Neural Output Feedback and Command Filtered Backstepping

This article is concerned with the tracking control problem for uncertain high-order nonlinear systems in the presence of input saturation. A finite-time control strategy combined with neural state observer and command filtered backstepping is proposed. The neural network models the unknown nonlinea...

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Bibliographic Details
Published inIEEE transaction on neural networks and learning systems Vol. 32; no. 4; pp. 1474 - 1485
Main Authors Zhao, Lin, Yu, Jinpeng, Wang, Qing-Guo
Format Journal Article
LanguageEnglish
Published United States IEEE 01.04.2021
The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subjects
Adaptive control
Adaptive filters
Adaptive neural control
Adaptive systems
Algorithms
Artificial Intelligence
Artificial neural networks
Backstepping
Computer Simulation
Control systems design
Dynamical systems
Error compensation
Feedback
Feedback control
Finite Element Analysis
finite-time control
Humans
input saturation
Neural networks
Neural Networks, Computer
Nonlinear control
Nonlinear Dynamics
Nonlinear systems
Observers
Output feedback
Saturation
State observers
Tracking control
Tracking errors
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Summary:This article is concerned with the tracking control problem for uncertain high-order nonlinear systems in the presence of input saturation. A finite-time control strategy combined with neural state observer and command filtered backstepping is proposed. The neural network models the unknown nonlinear dynamics, the finite-time command filter (FTCF) guarantees the approximation of its output to the derivative of virtual control signal in finite time at the backstepping procedure, and the fraction power-based error compensation system compensates for the filtering errors between FTCF and virtual signal. In addition, the input saturation problem is dealt with by introducing the auxiliary system. Overall, it is shown that the designed controller drives the output tracking error to the desired neighborhood of the origin at a finite time and all the signals in the closed-loop system are bounded at a finite time. Two simulation examples are given to demonstrate the control effectiveness.
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ISSN:2162-237X
2162-2388
2162-2388
DOI:10.1109/TNNLS.2020.2984773