Identification-based adaptive control for systems with time-varying parameters
File(s)
Accepted version
Author(s)
Chen, Kaiwen
Astolfi, Alessandro
Type
Conference Paper
Abstract
This paper proposes an identification-based adaptive control scheme for nonlinear systems with time-varying parameters designed on the basis of the so-called congelation of variables method. First a scalar example to demonstrate the design methodology, which relies on re-arranging the identifier subsystems from a cascaded topology to a cyclic topology, is discussed. A small-gain-like control synthesis exploiting the cyclic topology is then presented to replace the classical control synthesis based on the swapping lemma, which exploits the cascaded topology. Then a state feedback design for a class of lower triangular nonlinear systems is presented: this combines the same design methodology with the backstepping techniques. Boundedness of all closed-loop signals and convergence of the system state are proved. Finally, simulation results showing that the proposed controller achieves superior performance than the classical design are presented.
Date Issued
2022-02-01
Date Acceptance
2021-12-01
Citation
2021 60th IEEE Conference on Decision and Control (CDC), 2022, pp.1083-1088
ISSN
0743-1546
Publisher
IEEE
Start Page
1083
End Page
1088
Journal / Book Title
2021 60th IEEE Conference on Decision and Control (CDC)
Volume
2021-December
Copyright Statement
Copyright © 2021 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.
Source
60th IEEE Conference on Decision and Control (CDC)
Subjects
Automation & Control Systems
DESIGN
Engineering
Engineering, Electrical & Electronic
NONLINEAR-SYSTEMS
Science & Technology
Technology
Publication Status
Published
Start Date
2021-12-13
Finish Date
2021-12-17
Coverage Spatial
Austin, TX, USA (Virtual)