State and Fault Estimations for Discrete-Time T-S Fuzzy Systems With Sensor and Actuator Faults

This work investigates state and fault estimations (FEs) dedicated to nonlinear systems affected by sensor and constant actuator faults in the discrete-time domain. Takagi-Sugeno (T-S) fuzzy-approximation-based method is applied to express the concerned nonlinear dynamic. By augmenting the sensor fault and original state into a new form, a fuzzy observer is effectively synthesized to realize the reconstruction of this new state. Significantly, to reduce the conservatism of the convergence criterion of developed observer, the entire development of our paper is formulated in terms of using a fuzzy Lyapunov function. Besides, the state and FEs procedures are clearly given and presented as linear matrix inequalities (LMIs). Finally, simulation study on a real plant controlled by a DC motor is provided to show some potential applications of the developed technique.