A GPC controller robustification towards measurement noise and parameter uncertainty constrains

This paper presents a methodology for enhancing the robustness of a GPC controlled system by convex optimisation of the Youla parameter. This methodology requires, as a first step, the design of an initial GPC controller; this controller is then robustified considering frequency and temporal constraints. By means of the Youla parametrisation, frequency and temporal constraints are formulated within a convex optimisation framework, then the optimal parameter is deduced solving this optimisation problem. The developed robustified GPC controller is finally applied on a benchmark including an induction motor, aiming at reducing the impact of measurement noise and inertia variation of the system, while respecting a temporal template for the disturbance rejection. Comparison with results obtained with a ‘classical’ PID controller is finally given.