Fast Model Predictive Control Based on Formula Manipulation and Finite Step Prediction

Abstract

Model predictive control (MPC) in process control has shown its superior performance for tracking control. However, MPC has been applied mainly on larger scale plants because it requires high-performance computing environment. In this paper, we propose a novel approach for MPC based on formula manipulation and a finite-step prediction filter in order to achieve fast predictive control, which we can implement on edge-devices with low computing resources. We also propose a new approach to enhance regulatory control performance under unobservable disturbance, where a past prediction error filter and robust gain design are introduced. We discuss a convergence conditions and show numerical examples to validate the effectiveness of the proposed method.