Scenario-based Stochastic Model Predictive Control Design for an Electrohydraulic Actuator System

Abstract

In this paper, a novel scenario-based stochastic model predictive control design for an electrohydraulic actuator (EHA) system is proposed. The nonlinearity in the EHA system is approximated by parametric model uncertainties, and then the nonlinear dynamics is transmitted into a stochastic linear parameter varying (LPV) model. Based on this LPV model, a scenario-based stochastic model predictive control problem is formulated, and the constraints on the state and control input are taken into account as well. The resulting scenario optimization problem can be solved online efficiently by an advanced quadratic programming solver. Finally, the performance improvement of the proposed control scheme is demonstrated by numerical examples.