Fuzzy observer design for sampled nonlinear systems with measurement uncertainty

Abstract

In this paper, novel fuzzy observers are designed for a class of nonlinear systems with sampled outputs and unknown measurement noises. Firstly, sufficient conditions are given to ensure that a sampled‐data nonlinear system is ultimately uniformly bounded (UUB). Secondly, an output filtering transformation is taken. Then, an augmented nonlinear system is obtained. The sampled output and the measurement noise are transformed into the state equation of the augmented nonlinear system. Thirdly, an augmented observer is constructed by applying a fuzzy logic system (FLS) to approximate the unknown measurement noise. Sufficient conditions are derived by using a suitable Lyapunov–Krasovskii generalized function, such that the observation error is UUB. Finally, the effectiveness of the proposed method is verified by a numerical simulation example.