JOURNAL ARTICLE

Direct Model Reference Adaptive Fuzzy Control of Networked SISO Nonlinear Systems

Mojtaba Ahmadieh KhanesarYeşim ÖnizOkyay KaynakHuijun Gao

Year: 2015 Journal:   IEEE/ASME Transactions on Mechatronics Pages: 1-1   Publisher: Institute of Electrical and Electronics Engineers

Abstract

This study presents a novel direct model reference fuzzy controller as applied to the control of a nonlinear system over a network subject to variable network induced time delay. The proposed method uses Pade approximation to cope with this condition. Unlike most approaches seen in the literature, which are mostly model based and necessitate the solution of a set of linear matrix inequalities, the proposed approach is online and can be applied to nonlinear systems with a little knowledge about the structure of the system and the values of its parameters. The stability of the proposed method is proved using an appropriate Lyapunov function. The approach is implemented and tested on a dc motor with nonlinear characteristics and nonlinear state-dependent disturbance. It is shown that it is capable of controlling the system over a network subject to variable network-induced time delay with bounded tracking error. In addition, the effect of packet losses is considered in the implementation part and it is seen that the system can be controlled under these conditions too.

Keywords:
Control theory (sociology) Nonlinear system Computer science Variable (mathematics) State variable Controller (irrigation) Lyapunov function Bounded function Mathematics Control (management) Artificial intelligence

Metrics

32
Cited By
5.34
FWCI (Field Weighted Citation Impact)
34
Refs
0.96
Citation Normalized Percentile
Is in top 1%
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Citation History

Topics

Neural Networks Stability and Synchronization
Physical Sciences →  Computer Science →  Computer Networks and Communications
Chaos control and synchronization
Physical Sciences →  Physics and Astronomy →  Statistical and Nonlinear Physics
Adaptive Control of Nonlinear Systems
Physical Sciences →  Engineering →  Control and Systems Engineering
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