Sampled-Data Fuzzy Fault Estimation Observer Design for Nonlinear Systems

In this study, a sampled-data fuzzy fault estimation observer design problem is considered for nonlinear systems. The main idea of this study is to solve the sampled-data output problem by using two approaches of approximate discretization and exact discrete-time design. Especially, in the exact discrete-time design approach, the discretization error problem is solved, and the estimation error is minimized over whole time interval. Based on the above idea, the fuzzy fault estimation observer uses the Takagi–Sugeno fuzzy model to address the fuzzy fault estimation technique, and the fault estimation conditions with an
$H_{\infty }$
performance are guaranteed. Next, sufficient conditions of the proposed fault estimation techniques are converted into linear matrix inequality formats. Finally, two examples of circuit and oscillator systems are provided, and the effectiveness of the proposed fault estimation techniques is verified from results of the simulation.