Adaptive Robust Observer Design for a Class of Nonlinear Systems with Unmodeled Dynamics

In this paper an adaptive robust observer is designed for a class of uncertain nonlinear systems in presence of unmodeled dynamics. The proposed method is such that in presence of different kinds of uncertainties i.e. unknown parameters, uncertain nonlinearities, disturbance and unmodeled dynamics, the states of the system are approximated with high precision. In addition this method is designed so that one can apply to MIMO systems. Moreover, the proposed method requires only one adaptation parameters that make it easy to implement. It is also shown that the approximation error is uniformly bounded and it can be made small by designing appropriate parameters. Furthermore, the presented method neither requires the solution of Linear Matrix Inequalities (LMIs) nor to estimate unknown parameters. Simulation results on a sample system show that the norm of approximation error is bounded and the states of uncertain systems are efficiently approximated.