The State-of-the-art of Model Predictive Control in Recent Years

Abstract

Model predictive control is a control algorithm based on model and online application optimization performance. In the past 40 years, the feedback control strategy has been widely studied. However, with the rapid development of the economy, the requirements for online optimization and constrained performance have been improved, and the current model predictive control theory can not meet the demand any more. This paper first briefly describes the current situation of model prediction, industrial development, and application areas, and then analyzes the limitations of theory and technology at the current stage, then proposes the significance of the study of predictive control of large-scale systems, fast dynamic systems, and nonlinear systems for the development of model predictions.