Probabilistic Robust LPV Control

The contribution of this paper is a probabilistic synthesis method for robust linear parameter-varying control. Driven by the issues of deterministic robust synthesis algorithms, the chief idea is to combine robust control theory and convex optimization results with probabilistic relaxation and randomized algorithms. The proposed algorithm is a randomized extension of the loop-shaping procedure by McFar-lane and Glover. Gain-scheduling with respect to measurable and robustness against uncertain parameters, possibly entering the system dynamics nonlinearly, are tackled via sampling techniques similar to Monte Carlo. The algorithm is validated by an application example from aerospace.