A Robust Predictive Control Design for Nonlinear Active Suspension Systems

Abstract

This paper proposes a novel method for designing robust nonlinear multivariable predictive control for nonlinear active suspension systems via the Takagi-Sugeno fuzzy approach. The controller design is converted to a convex optimization problem with linear matrix inequality constraints. The stability of the control system is achieved by the use of terminal constraints, in particular the Constrained Receding-Horizon Predictive Control algorithm to maintain a robust performance of vehicle systems. A quarter-car model with active suspension system is considered in this paper and a numerical example is employed to illustrate the effectiveness of the proposed approach. The obtained results are compared with those achieved with model predictive control in terms of robustness and stability.