Robust fault detection and isolation scheme using fuzzy wavelet network with a hybrid design algorithm

Abstract

This paper presents a new robust fault detection and isolation scheme using fuzzy wavelet network based on the bounded error approach. An ecient hybrid design algorithm, which consists of the orthogonal least square and the arti cial bee colony algorithms, is proposed to design fuzzy wavelet network for modeling normal and faulty behaviors of the system. The proposed model provides an alternative description of the behavior of the system with high accuracy, but it su ers from model uncertainty because of model-reality mismatch in practical applications. To overcome this diculty, the bounded error approach inspired from robust identi cation theory is applied to estimate the model uncertainty which de nes a con dence interval of the model output and derives adaptive threshold for residual evaluation. Also, online fault isolation process is performed using fuzzy wavelet network models of the faulty system and analyzing the relation between a bank of residuals. Performance and eciency of the proposed scheme is evaluated by simulating the nonlinear two-tank liquid level control system. Finally, some performance indexes are de ned, and then the Monte-Carlo analysis is carried out to evaluate the reliability and robustness of the proposed scheme.