State and sensor fault reconstruction with H∞ performance for lipschitz nonlinear systems with time varying uncertainties

This paper presents a scheme for simultaneously estimating state and sensor fault for a class of uncertain nonlinear systems whose nonlinear function satisfies the Lipschitz condition with unknown inputs and time-varying uncertainties. The effects of the system unknown input and the sensor fault derivative on the estimation errors of states are reduced by integrating a prescribed disturbance attenuation level into the proposed scheme. The proposed design is derived and expressed as Linear Matrix Inequality optimization problem (LMI). The proposed observer parameters are determined by using LMI techniques. The effectiveness of this scheme in estimating sensor fault is clarified by considering an example of a single-link manipulator. The simulation results attested that the proposed approach can estimate state and sensor fault successfully even in the presence of unknown input and system time varying uncertainties.