Fault detection in nonlinear systems based on type-2 fuzzy sets and bat optimization algorithm

Article type: Research Article

Authors: Safarinejadian, Behrouz | Bagheri, Bahareh | Ghane, Parisa

Affiliations: Electrical and Electronic Engineering Department, Shiraz University of Technology, Shiraz, Iran

Note: [] Corresponding author. Behrouz Safarinejadian, Electrical and Electronic Engineering Department, Shiraz University of Technology, Modarres Blvd., 71555-313 Shiraz, Iran. E-mail: safarinejad@sutech.ac.ir

Abstract: In this paper, a new method of fault detection is proposed based on interval type-2 fuzzy systems. The main idea is to provide a confident span using interval type-2 fuzzy sets. Bat algorithm, as a metaheuristic method, is used to optimize the parameters of the system. In other words, upper and lower bounds of the interval type-2 fuzzy system are estimated by means of two optimal fuzzy functions. The proposed fault detection method has been tested in a non-linear system, a two-tank with a fluid flow. Simulation results show that the proposed method is very strong and effective.

Keywords: Fuzzy system, interval type-2 fuzzy, bat algorithm, fault detection

DOI: 10.3233/IFS-141288

Journal: Journal of Intelligent & Fuzzy Systems, vol. 28, no. 1, pp. 179-187, 2015