The extended state filter for a class of multi-input multi-output nonlinear uncertain hybrid systems

This paper proposes a novel filter, the Extended State Filter(ESF), for a class of multi-input multi-output(MIMO) nonlinear systems with the continuous uncertain dynamics and the discrete measurement polluted by noise. It is proven that the covariance of the filtering error converges despite the nonlinear time-varying uncertainties in the system, and the filtering precision can be timely evaluated by the filter´s parameters. Additionally, ESF is shown to be the linear minimum variance filter if the uncertainties are constant. The feasibility and effectiveness of ESF are illustrated by the simulation on a nonlinear spring-mass-damper system.