Predictive Control of a helicopter model with tolerance to actuator faults

Predictive Control formulations can be designed with nominal asymptotic stability guarantees, provided that the associated optimization problem is feasible at each sampling time. However, model-plant mismatches, external perturbations or faults may cause the optimization to become infeasible. Such a problem motivates the development of techniques aimed at recovering feasibility without violating hard physical constraints imposed by the nature of the plant. This paper investigates the possible advantages of employing a policy of setpoint management to circumvent infeasibility problems in a Predictive Control framework. The investigation is mainly concerned with robustness of the controller regarding actuator faults that can be modelled as a change in the allowed excursion of the control signal. The results obtained with the proposed setpoint management technique are compared to the default solution provided by the adopted computational toolbox in case of infeasibility. An application involving a nonlinear simulation model of a laboratory helicopter with three degrees of freedom is presented.