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Data‐driven adaptive terminal sliding mode control with prescribed performance
Author(s) -
Hou Mingdong,
Wang Yinsong
Publication year - 2021
Publication title -
asian journal of control
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.769
H-Index - 53
eISSN - 1934-6093
pISSN - 1561-8625
DOI - 10.1002/asjc.2245
Subject(s) - control theory (sociology) , terminal sliding mode , tracking error , terminal (telecommunication) , convergence (economics) , sliding mode control , tracking (education) , computer science , nonlinear system , trajectory , adaptive control , mode (computer interface) , scheme (mathematics) , function (biology) , control (management) , mathematics , artificial intelligence , psychology , telecommunications , pedagogy , mathematical analysis , physics , quantum mechanics , astronomy , evolutionary biology , economics , biology , economic growth , operating system
We propose a novel data‐driven model‐free adaptive terminal sliding mode control (SMC) for a class of discrete nonlinear systems with perturbations in which tracking error constraints are taken into account in improving tracking accuracy. The goal of this design is that the tracking error trajectory is maintained within the prescribed convergence region which is defined by the performance function, while the disturbances exist. In explaining the advantage of this proposed control scheme, at first, by theoretical calculation, it is proved theoretically that the quasi‐sliding mode can be achieved in a limited time under the specified tracking performance. Furthermore, comparative investigation results are given to validate the effectiveness of the proposed control scheme. Simulation results show that the proposed strategy is superior to model‐free adaptive control, model‐free adaptive terminal SMC, and data‐driven adaptive SMC with prescribed performance control algorithms in terms of tracking accuracy and response speed, which demonstrates the efficiency of the proposed scheme.