Control of an Autonomous Hybrid System Using a Nonlinear Model Predictive Controller

State estimation and estimator based predictive control of nonlinear autonomous hybrid systems poses a challenging problem as these systems involve discontinuities that are introduced by switching of the discrete variables. In this paper, we propose a state estimation scheme for an autonomous hybrid system using an ensemble Kalman filter (EnKF), which belongs to the class of particle filters and is a derivative free nonlinear state estimator. We then proceed to develop a novel nonlinear model predictive control scheme that inherits the approach used in EnKF formulation for future trajectory predictions. The efficacy of the proposed state estimation and control scheme is demonstrated by conducting simulation studies on a benchmark hybrid three-tank system.