Model REFERENCE Tracking Control for Uncertain Takagi-Sugeno Systems subject to Sensor Faults

摘要

This work concerns the model REFERENCE fault tolerant tracking Control problem for uncertain Takagi-Sugeno (T-S) models with unmeasurable premise variables. The idea is to synthesize a fault tolerant controller with a guaranteed ° performance to attenuate the tracking error for bounded REFERENCE inputs. Based on Lyapunov theory, new less conservative approach is proposed in terms of Linear Matrix Inequalities (LMIs). A descriptor observer is needed to estimate simultaneously the sensor faults and the system states in order to reconfigure the FTC law. A numerical example is considered to illustrate the effectiveness of the proposed FTC tracking performance approach.