Open AccessAdaptive neural control for a class of time‐delay systems in the presence of backlash or dead‐zone non‐linearity
Author(s) -
Liu Zongcheng,
Dong Xinmin,
Xue Jianping,
Chen Yong
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.2013.0903
Subject(s) - control theory (sociology) , linearity , backlash , actuator , mathematics , bounded function , residual , controller (irrigation) , computer science , artificial neural network , control (management) , engineering , algorithm , artificial intelligence , mathematical analysis , agronomy , electrical engineering , biology
This study addresses the adaptive tracking control problem for a class of time‐delay systems in strict‐feedback form with unknown control gains and uncertain actuator non‐linearity. The actuator non‐linearity can be either backlash or dead zone, and the proposed approach does not require the knowledge of the bounds of non‐linearity parameters. By applying an appropriate Lyapunov–Krasovskii functional and utilising the property of the well‐defined trigonometric functions, the problems of time delay and controller singularity are avoided. The feasibility of using a static neural network to attenuate the effect of actuator non‐linearity is proved with the aid of intermediate value theorem. Furthermore, it is proved that all closed‐loop signals are bounded and the tracking error converges to a small residual set asymptotically. Two simulation examples are provided to demonstrate the effectiveness of the designed method.