Multi-Input Multi-Output Model-Free Predictive Control and Its Application to Wastewater Treatment

Model-free predictive control is a data-driven control method that directly computes the control input from massive input/output datasets. It does not require the mathematical models that are used in conventional model predictive control. It has recently been shown that the control offered by model-free predictive control can be improved by the introduction of polynomial regression vectors containing the control input and measurement output. In this paper, we extend these findings to multi-input multi-output nonlinear systems and investigate the effectiveness of the approach through numerical simulations of a wastewater treatment process. (C) 2017 Institute of Electrical Engineers of Japan. Published by John Wiley & Sons, Inc.