Title: An adaptive approach for the fault tolerant control of a nonlinear system

Authors: K. Sudha; V. Thulasi Bai

Addresses: St. Peter's University, Chennai, India ' Department of Electronics and Communication in the Engineering, Pratyusha Institute of Technology and Management, Chennai, India

Abstract: In this paper hybridisation between two optimisation methods such as modified bacterial foraging optimisation algorithm (MBFOA) and adaptive neuro fuzzy inference system (ANFIS) is presented for determining the optimal proportional-integral (PI) controller parameters, for fault tolerant control (FTC) in an wind energy conversion system (WECS). Initially, detection and diagnosis of fault is performed by the ANFIS. The wind turbine actual output performance and the estimated output values are given as an input to the ANFIS. The residuals, which are the outputs of ANFIS is used for deciding, whether the signal is a fault signal or a non-fault signal, which utilises the knowledge-based computation technique. By using the step size modified bacterial foraging optimisation algorithm-based FTC, the gain parameters are optimised based on the occurrence of fault. Then the proposed hybrid fault tolerant control model is implemented in the MATLAB/SIMULINK platform and the effectiveness is analysed by comparing with the other techniques. The comparison results demonstrate the superiority of the proposed approach and confirm its potential in controlling the fault in a WECS.

Keywords: bacterial foraging optimisation algorithm; BFOA; wind energy conversion systems; WECS; fault detection and diagnosis; FDD; fault diagnosis; fault tolerant control; FTC; fault tolerance; adaptive control; nonlinear systems; wind power; adaptive neuro fuzzy inference systems; ANFIS; fuzzy logic; neural networks; PI control; wind turbines; simulation.

DOI: 10.1504/IJAAC.2017.083299

International Journal of Automation and Control, 2017 Vol.11 No.2, pp.105 - 123

Received: 03 Sep 2015
Accepted: 07 May 2016
Published online: 23 Mar 2017 *

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