Title: Delayed model-free adaptive control with prescribed performance and external disturbance based on DESO

Authors: Yujuan Wang; Jiahui Huang; Chao Shen; Hua Chen

Addresses: Nanjing Vocational College of Information Technology, Nanjing, China ' School of Mathematics, Hohai University, Nanjing, China ' School of Mathematics, Hohai University, Nanjing, China ' School of Mathematics, Hohai University, Nanjing, China

Abstract: A new data-driven model-free adaptive control is proposed for the discrete-time nonlinear system with input time delay and bounded external disturbance, and the tracking error constraint is considered to improve the tracking accuracy. Firstly, the original nonlinear time delay system is transformed into a data model by applying the partial-form dynamic linearisation (PFDL) method. Secondly, the discrete-time extended state observer (DESO) is applied to estimate the unknown residual nonlinear time-varying term. In addition, a novel transformed error algorithm and a new sliding mode control framework are studied to ensure the tracking error converges to the preset region. A DESO-based PFDL prescribed performance control (PPC) is proposed to ensure that the tracking error always converges to a prescribed zone, which is important and considerable in practical engineering applications. Finally, some numerical simulations prove the effectiveness of the proposed control methods.

Keywords: model-free adaptive control; prescribed performance control; PPC; disturbance; time delay; discrete-time extended state observer.

DOI: 10.1504/IJMIC.2024.142281

International Journal of Modelling, Identification and Control, 2024 Vol.45 No.2/3, pp.85 - 99

Received: 20 Sep 2023
Accepted: 29 Feb 2024
Published online: 16 Oct 2024 *

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