Relaxing the control-gain assumptions of DSC design for nonlinear MIMO systems

Conference paper (2019)

Authors

Yong Chen Air Force Engineering University
Maolong Lv Team Bart De Schutter - Mechanical, Maritime and Materials Engineering
S. Baldi Southeast University, Team Bart De Schutter - Mechanical, Maritime and Materials Engineering
Zongcheng Liu Air Force Engineering University
Wenqian Zhang Air Force Engineering University
Yang Zhou Air Force Engineering University
Research Group
Team Bart De Schutter (Mechanical, Maritime and Materials Engineering) (TU Delft)
Copyright: © 2019 Yong Chen, Maolong Lv, S. Baldi, Zongcheng Liu, Wenqian Zhang, Yang Zhou
Backstepping Stability analysis Nonlinear systems Control design MIMO communication Adaptive systems
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Published Date

2019

Language

English

Reuse Rights

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Faculty

Mechanical, Maritime and Materials Engineering

Department

Delft Center for Systems and Control

Research Group

Team Bart De Schutter

Abstract

This work focuses on adaptive neural dynamic surface control (DSC) for an extended class of nonlinear MIMO strict-feedback systems whose control gain functions are continuous and possibly unbounded. The method is based on introducing a compact set which is eventually proved to be an invariant set: thanks to this set, the restrictive assumption that the upper and lower bounds of control gain functions must be bounded is removed. This method substantially enlarges the class of systems for which DSC can be applied. By utilizing Lyapunov theorem and invariant set theory, it is rigorously proved that all signals in the closed-loop systems are semi-globally uniformly ultimately bounded (SGUUB) and the output tracking errors converge to an arbitrarily small residual set. A simulation example is provided to demonstrate the effectiveness of the proposed approach.

Files

ASCC19_0216_FI2.pdf
(.pdf | 0.451 Mb)