Fuzzy Decision In H∞ State Estimation For Model Predictive Control

Model predictive control (MPC) has emerged as a powerful practical control technique over the past few years. Due to the difficulties arising in state estimations in state-space MPC algorithms, an H∞ state estimation approach were used in the current work that can give a controlled estimated states to the algorithm. To do this control task, a fuzzy supervisor was designed to control the value of γ, H∞ tuning coefficient. An industrial process 'heavy oil fractionator' was used for simulation. The results demonstrated the improved performance of the approach both in tracking and disturbance rejection capabilities.

Keywords:

Model Predictive Control , H∞ state estimation , Fuzzy decision