模型预测控制——现状与挑战

30多年来, 模型预测控制(Model predictive control, MPC)的理论和技术得到了长足的发展, 但面对经济社会迅速发展对约束优化控制提出的不断增长的要求, 现有的模型预测控制理论和技术仍面临着巨大挑战. 本文简要回顾了预测控制理论和工业应用的发展, 分析了现有理论和技术所存在的局限性, 提出需要加强预测控制的科学性、有效性、易用性和非线性研究. 文中简要综述了近年来预测控制研究和应用领域发展的新动向, 并指出了研究大系统、快速系统、低成本系统和非线性系统的预测控制对进一步发展预测控制理论和拓宽其应用范围的意义.

Model Predictive Control——Status and Challenges

Since last 30 years the theory and technology of model predictive control (MPC) have been developed rapidly. However, facing to the increasing requirements on the constrained optimization control arising from the rapid development of economy and society, the current MPC theory and technology are still faced with great challenges. In this paper, the development of MPC theory and industrial applications is briefly reviewed and the limitations of current MPC theory and technology are analyzed. The necessity to strengthen the MPC research around scientificity, effectiveness, applicability and nonlinearity is pointed out. We briefly summarize recent developments and new trends in the area of MPC theoretical study and applications, and point out that to study the MPC for large scale systems, fast systems, low cost systems and nonlinear systems, will be significant for further development of MPC theory and broadening MPC application fields.