Research Papers

An Adaptive Fuzzy H Synergetic Approach to Robust Control

[+] Author and Article Information
L. Medjbeur

QUERE Laboratory,
Electrical Engineering Department,
Ferhat Abbas University of Sétif1,
Sétif 19000, Algeria
e-mail: lemya_medjbeur@yahoo.fr

M. N. Harmas

QUERE Laboratory,
Electrical Engineering Department,
Ferhat Abbas University of Sétif1,
Sétif 19000, Algeria
e-mail: mharmas@yahoo.fr

S. Benaggoune

LRE Laboratoire des systèmes
de traction électrique,
Hadj Lakhdar University of Batna,
Batna 05010, Algeria
e-mail: s_benaggoune@yahoo.fr

K. Zehar

Department of Electrical and
Electronic Engineering,
Bahrain University,
Zallaq 32038, Bahrain
e-mail: kzehar@uob.edu.bh

Contributed by the Dynamic Systems Division of ASME for publication in the JOURNAL OF DYNAMIC SYSTEMS, MEASUREMENT, AND CONTROL. Manuscript received February 5, 2016; final manuscript received June 29, 2017; published online September 8, 2017. Assoc. Editor: Srinivasa M. Salapaka.

J. Dyn. Sys., Meas., Control 140(1), 011008 (Sep 08, 2017) (7 pages) Paper No: DS-16-1078; doi: 10.1115/1.4037330 History: Received February 05, 2016; Revised June 29, 2017

Robust control often requires some adaptive approach in evaluating systems dynamics to handle parameters variations and external disturbances. Therefore, an error due to dynamics approximation is inevitably added to uncertainties already present in the model. This issue is addressed in this paper, through the combination of two robust techniques, Hinf and synergetic control. These latter are used to ensure reducing tracking error in the overall closed-loop system while guaranteeing stability via Lyapunov synthesis. With the aim of handling parameters variations, an indirect adaptive fuzzy scheme is used to elaborate system model. Simulation studies are conducted to assess the proposed approach on two practical systems, and the results are compared to a sliding mode proportional integral (PI)-based technique. It is to be noted that a large class of systems depicted as control affine systems will be considered in this paper. An induction motor and an inverted pendulum representing, respectively, a linear and a nonlinear system are utilized in this study showing improvement due to the suggested approach, in overall performance over its sliding mode control counterpart.

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Grahic Jump Location
Fig. 1

System output and reference

Grahic Jump Location
Fig. 3

System output and reference

Grahic Jump Location
Fig. 5

System output and reference




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