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Design of disturbance observer based on adaptive‐neural control for large‐scale time‐delay systems in the presence of actuator fault and unknown dead zone
Author(s) -
Janbazi Vida,
Hashemi Mahnaz
Publication year - 2021
Publication title -
international journal of adaptive control and signal processing
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.73
H-Index - 66
eISSN - 1099-1115
pISSN - 0890-6327
DOI - 10.1002/acs.3204
Subject(s) - control theory (sociology) , backstepping , actuator , nonlinear system , computer science , compensation (psychology) , lyapunov function , observer (physics) , dead zone , artificial neural network , adaptive control , control (management) , artificial intelligence , psychology , oceanography , physics , quantum mechanics , psychoanalysis , geology
Summary This article presents an adaptive neural compensation scheme for a class of large‐scale time delay nonlinear systems in the presence of unknown dead zone, external disturbances, and actuator faults. In this article, the quadratic Lyapunov–Krasovskii functionals are introduced to tackle the system delays. The unknown functions of the system are estimated by using radial basis function neural networks. Furthermore, a disturbance observer is developed to approximate the external disturbances. The proposed adaptive neural compensation control method is constructed by utilizing a backstepping technique. The boundedness of all the closed‐loop signals is guaranteed via Lyapunov analysis and the tracking errors are proved to converge to a small neighborhood of the origin. Simulation results are provided to illustrate the effectiveness of the proposed control approach.