Adaptive multi-model predictive control applied to continuous stirred tank reactor. (February 2021)

• Record Type: Journal Article
• Authors: Pipino, Hugo A.; Cappelletti, Carlos A.; Adam, Eduardo J.
• Is Part Of: Computers & chemical engineering. Volume 145(2021)
• Publication Date: 2021-02
• Subjects: Model predictive control -- Multi-model systems -- Stability -- Feasibility -- CSTR; Chemical engineering -- Data processing -- Periodicals; 660.0285
• DOI: 10.1016/j.compchemeng.2020.107195
• Languages: English
• ISSNs: 0098-1354

Abstract

Abstract: This paper investigates the design of a Model Predictive Control ( MPC ) formulation for the case of polytopic multi-model system representation. An adaptive MPC is developed taking into account the scheduling 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 reactor (CSTR) system. Discussions are set upon the a-priori design procedure, the online computational effort and application difficulties.