Mehran Shakarami1, Kasra Esfandiari2, Amir Abolfazl Suratgar3, H.A. Talebi4
11:20 - 11:40 | Mon 17 Dec | Splash 7-8 | MoA16.5
In this paper a novel method is proposed for state estimation of nonlinear systems using high-gain observers (HGOs) and adaptive techniques. In this regard, Multiple HGOs (MHGO) are run simultaneously, and the information obtained from individual observers are combined adaptively. To be able to suitably combine the state estimations, it is first proved that there exist some constant coefficients that provide the perfect estimation. Then, the RLS algorithm is employed to find those coefficients. The convergence of the state estimations to the system states is guaranteed, and it is shown that the MHGO is able to attenuate the inherent peaking phenomenon in HGOs. Finally, the simulation results are presented which show the superiority of the proposed MHGO method in state estimation and improving the transient response.