Abstract
In this paper, we consider problems of state estimation, unknown input, and measurement noise reconstruction for a class of Lipschitz nonlinear systems. By extending the measurement noise as an auxiliary state vector, the original system is transformed into an augmented descriptor system. Then an adaptive H ∞ observer is developed for estimating the states, unknown input and measurement noise simultaneously. Further, sufficient conditions of the existence of the adaptive H ∞ observer are given in the form of linear matrix inequality, which can be solved easily via some efficient mathematic tools. Finally, two simulation examples are given to illustrate the effectiveness of the proposed method.
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