Supervisory Takagi-Sugeno Fuzzy Fault-Tolerant Control of a Rail Traction System

摘要

This paper investigates the development of a supervisory control system with qualitative tasks at the upper level and simple quantitative models at the lower level to control complex non-linear systems. A new quantitative approach for thestability 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 stability of fuzzymodels for both T-S fuzzy observers and T-S fuzzy controllers together are derived. The problem is solved via the Linear Matrix Inequality (LMI) method. The paper demonstrates the feasibility of this system architecture through application to afault-tolerant design for a railway traction system using DSP in a hardware test-rig.