Nonlinear predictive reference governor for constrained control systems

This paper presents a new methodology for solving control problems where hard contraints on the state and/or the inputs of the system are present. This is achieved by adding to the control architecture a command governor which prefilters the reference to be tracked, taking into account the current value of the state and aiming at optimizing a tracking performance index. The overall system is proved to be asymptotically stable, and feasibility is ensured by a weak condition on the initial state linear loops, a complete solution is developed for the latter. The resulting online computational burden turns out to be moderate and the related operations executable with current low-priced computing hardware.