Generalized Predictive Control (GPC) is a multi-step approach. It combines feed-forward part and feedback part. The feed-forward part is represented by prediction via mathematical model describing a controlled system. This part forms the dominant part of control actions. The feedback, closed from measured outputs, compensates some inaccuracies of the model and certain bounded disturbances.
The real design consists in composition of equations of predictions and minimization of quadratic criterion, in which the equations of predictions are involved. The minimization is performed within finite horizons.
The research is focused on state-space control design applied to deterministic linear systems, deterministic nonlinear systems and slightly stochastic systems. Developed control algorithms are tested on mechanical systems as industrial robotic structures.
Basic algorithms of predictive control are available in GPC toolbox for MATLAB&Simulink. The toolbox contains both m-functions and c-coded functions and Simulink schemes.