Supervisory fault tolerant system using fuzzy multiple inference modelling

This paper presents a novel approach to integrating quantitative and qualitative information in fault-diagnosis. This paper investigates the development of a supervisory control scheme for a non-linear system with qualitative tasks at the upper level and a lower level comprising quantitative model based non-linear control. A new quantitative approach for the stability of non-linear fuzzy inference systems using Takagi-Sugeno (T-S) fuzzy models is presented. The necessary conditions for the assignability of eigenvalues to a region in the s-plane and the necessary conditions to guarantee the joint stability of fuzzy models for combined T-S fuzzy observers and T-S fuzzy controllers together are derived.