Robust Fault Detection and Isolation Scheme Using Fuzzy Wavelet Network with a Hybrid Design Algorithm

This paper presents a new robust fault detection and isolation scheme using fuzzy wavelet network based on the bounded error approach. An efficient hybrid design algorithm which consists of the orthogonal least square and the artificial bee colony algorithm is proposed to design fuzzy wavelet network for modeling normal and faulty behavior of the system. The proposed model provides an alternative description of the behavior of the system with high accuracy, but it suffers from model uncertainty, because of model-reality mismatch in practical applications. To overcome this difficulty, the bounded error approach inspired from robust identification theory, is applied to estimate the model uncertainty which defines a confidence 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 efficiency of the proposed scheme is evaluated by simulating the nonlinear two-tank liquid level control system. Finally, some performance indexes are defined and then the Monte-Carlo analysis is carried out to evaluate the reliability and robustness of the proposed scheme.