Abstract :
In this work, it is proposed an MPC control algorithm with proved robust stability for systems with model uncertainty and output
feedback. It is assumed that the operating strategy is such that system inputs may become saturated at transient or steady state.
The developed strategy aims at the case in which the controller performs in the output-tracking scheme following an optimal set
point that is provided by an upper optimization layer of the plant control structure. In this case, the optimal operating point usually
lies at the boundary of the region where the input is defined. Assuming that the system remains stabilizable in the presence of input
saturation, the design of the robust controller is performed off-line and an on-line implementation strategy is proposed. At each
sampling step, a sub optimal control law is obtained by combining control configurations that correspond to particular subsets
of available manipulated inputs. Stability of the closed-loop system is forced by considering in the off-line step of the controller
design, a state contracting restriction for the closed-loop system. To produce an offset free controller and to attend the case of
unknown steady state, the method is developed for a state-space model in the incremental form. The method is illustrated with simulation
examples extracted from the process industry.
Keywords :
Robust stability , Model predictive control , Saturated input , Output feedback