A mixed-integer model predictive control formulation for linear systems

作     者：Moro, Lincoln F. L. Grossmann, Ignacio E. 

作者机构：Petrobras SA Sao Paulo Brazil Carnegie Mellon Univ Pittsburgh PA 15213 USA 

出 版 物：《COMPUTERS & CHEMICAL ENGINEERING》 (Comput. Chem. Eng.)

年 卷 期：2013年第55卷

页      面：1-18页

核心收录：

学科分类：0817[工学-化学工程与技术] 08[工学] 0812[工学-计算机科学与技术（可授工学、理学学位）] 

主　　题：Mixed integer programming Predictive control Hybrid control 

摘      要：Since their inception in the early 1980s industrial model predictive controllers (MPC) rely on continuous quadratic programming (QP) formulations to derive their optimal solutions. More recent advances in mixed-integer programming (MIP) algorithms show that MIP formulations have the potential of being advantageously applied to the MPC problem. In this paper, we present an MIP formulation that can overcome difficulties faced in the practical implementation of MPCs. In particular, it is possible to set explicit priorities for inputs and outputs, define minimum moves to overcome hysteresis, and deal with digital or integer inputs. The proposed formulation is applied to simulated process systems and the results compared with those achieved by a traditional continuous MPC. The solutions of the resulting mixed-integer quadratic programming (MIQP) problems are derived by a computer implementation of the Outer Approximation method (OA) also developed as part of this work. (C) 2013 Elsevier Ltd. All rights reserved.