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Adaptive non‐backstepping fuzzy tracking control for a class of multiple‐input–multiple‐output pure‐feedback systems with unknown dead‐zones
Author(s) -
Wang Rui,
Yu Fu Sheng,
Wang Jia Yin
Publication year - 2014
Publication title -
iet control theory and applications
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.059
H-Index - 108
eISSN - 1751-8652
pISSN - 1751-8644
DOI - 10.1049/iet-cta.2014.0059
Subject(s) - control theory (sociology) , backstepping , strict feedback form , computation , observer (physics) , computer science , unavailability , adaptive control , fuzzy logic , tracking error , fuzzy control system , mathematics , control (management) , algorithm , artificial intelligence , statistics , physics , quantum mechanics
In this study, the authors present a novel adaptive non‐back‐stepping alleviating computation tracking control algorithm for a class of MIMO pure‐feedback systems with unknown dead‐zone inputs. Based on the introduced new state variables and coordinate transforms, the pure‐feedback form is converted into a normal form where back‐stepping scheme is not necessary. Owing to the unavailability of the new states, the tracking control problem is changed from a state‐feedback one to an output‐feedback one. Therefore, observers need to be designed to estimate the indirect un‐measurable states. In the controller and observer design procedure, the control method is based on non‐back‐stepping scheme and for each subsystem only three adaptive adjusted parameters are needed to be updated on‐line. Thus, different from the back‐stepping‐based ones, this new algorithm can not only alleviate on‐line computation burden but also can considerably simplify the control procedure. According to Lyapunov stable analysis methods, the bounded of all the signals in the closed‐loop system can be guaranteed and the tracking error is proven to converge to a small neighbourhood of the origin. Simulation results are presented to illustrate the effectiveness of this proposed approach.

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