Polynomial regression based model-free predictive control for nonlinear systems

Abstract

In this paper, we introduce model-free predictive control based on a polynomial regression expression for nonlinear systems. In contrast to conventional methods, model-free predictive control does not explicitly require a mathematical model of the controlled systems. In stead of the model, it utilizes massive stored and observed input/output dataset to predict the optimal control input. To date, the model-free predictive control method is based on linear regression vectors of the input/output data. Here we extend the method to polynomial regression vectors. By numerical simulations, we illustrate the effectiveness of model-free predictive control.