Model Predictive Control for Tracking - Rajasegaan, Sarasuwathi (IRC, 2016)
Model predictive control (MPC) is a successful technique which enables to deliver the desired goals specified for the controlled process. Having the prediction ability, when combined with traditional feedback operation, it enables to make adjustments that are stable and closer to the optimal of set-points. MPC controller often employs cost functions with varying economic conditions. One to frequent changes in the economics of the plant, the optimal steady states continuously changes. Funct ion of MPC is to compute a sequence of control moves so that the predicted system response moves as close to the set point by reducing the error. The objective of this project is to analyze the response and the effect of tuning parameters on the control system performance of tracking MPC controllers. The results of this project show the effect of tuning parameters on the control system as well as the tracking ability for different scenarios