Adaptive multi-model predictive control applied to continuous stirred tank reactor

Abstract

This paper investigates the design of a Model Predictive Control ( MPC ) formulation for the case of poly- topic multi-model system representation. An adaptive MPC is developed taking into account the schedul- ing parameters in the multi-model and a terminal invariant set for all the systems that are within the system polytope. This proposed method uses a virtual model-process tuning variable, which is optimized to find the best Linear Time Invariant ( LTI ) prediction sequence for the horizon, based on the LTI vertices of the polytopic system. Finally, the proposed adaptive MPC is applied to a continuous stirred tank reac- tor (CSTR) system. Discussions are set upon the a-priori design procedure, the online computational effort and application difficulties.