Optimization‐based adaptive control for MIMO nonlinear systems: A data‐driven method
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Published:2023-10-18
Issue:3
Volume:34
Page:1522-1540
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ISSN:1049-8923
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Container-title:International Journal of Robust and Nonlinear Control
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language:en
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Short-container-title:Intl J Robust & Nonlinear
Author:
San Yang1,
Hui Yu1ORCID,
Cai Kaiquan2,
Meng Deyuan1
Affiliation:
1. School of Automation Science and Electrical Engineering Beihang University (BUAA) Beijing People's Republic of China
2. School of Electronics and Information Engineering Beihang University (BUAA) Beijing People's Republic of China
Abstract
AbstractThis article concentrates on the challenging adaptive tracking problem of multi‐input and multi‐output (MIMO) nonlinear systems with unknown nonlinear dynamics, for which a novel optimization‐based data‐driven adaptive control (ODDAC) equipped with an extended dynamic linearization method is developed. Through considering MIMO nonlinear systems in the fully‐actuated case and over‐actuated case separately, the ODDAC is proposed consisting of a parameter updating algorithm and an adaptive control law. A new design of parameter updating algorithm is presented such that the estimation can be guaranteed to be bounded by a strict contraction process. By leveraging properties of the nonnegative matrix, a grouping‐based contraction mapping (GCM) analysis method is proposed for the convergence of tracking error. Notably, the GCM does not require the contraction mapping condition to hold at all time instants. The proposed ODDAC is data‐based, avoiding reliance on model information, and its validity is verified through simulations.
Funder
National Key Research and Development Program of China
National Natural Science Foundation of China
China Postdoctoral Science Foundation
Subject
Electrical and Electronic Engineering,Industrial and Manufacturing Engineering,Mechanical Engineering,Aerospace Engineering,Biomedical Engineering,General Chemical Engineering,Control and Systems Engineering