A Novel Tuning Approach for MPC Parameters Based on Artificial Neural Network: An application to FOPDT System

Abstract : A successful implementation of Model Predictive Control (MPC) requires appropriately tuned parameters. In this paper an Artificial-Neural-Network (ANN) based approach is presented and detailed in the case of a First Order Plus Dead Time (FOPDT) control-lable system. The original part of our approach lies in its capability to tune the MPC parameters using Particle-Swarm-Optimization (PSO) and Online-Sequential-Extreme-Learning-Machine(OS-ELM). This approach allows also to reach efficiently closed-loop stability. The effectiveness of our approach has been emphasized by comparing the obtained performances to other existing methods.