Simulation and Research for Generalized Predictive Control

This paper presents analysis and experiments for Generalized Predictive Control (GPC) algorithm based on software simulation. First, we illustrate the time invariant GPC algorithm in detail. Then, we describe the principle for the control parameter selection of GPC based on empirical results. The Recursive Least Square (RLS) algorithm will be used to identify model parameters in the self-tuning GPC. The performance of GPC algorithm is validated by simulation results, which show that the algorithm has rapid and accurate dynamic responses for input signals, such as step signal and square wave. When the model parameters are unknown, with the assistance of RLS, the self-tuning GPC algorithm also presents good performance and robustness capability, even when white Gaussian noise exists.