Modulating robustness in robust control: Making it easy through randomization

Reportedly, robust control can lead to designs that are overconservative because all emphasis is placed on safe-guarding the designed closed-loop against all possible doomy occurrences, and this is done at the price of sacrificing performance. When 100% guarantee of robustness is required, standard robust control is indeed the way to go. However, in many applications, robustness in 100% of the cases is not really necessary and it is a fact that accepting a small compromise in robustness guarantees (e.g. accepting a 99% guarantee) can often times lead to a huge improvement in performance. At the present stage of knowledge, the real stumbling-block is the lack of computationally-tractable algorithmic methods to work out 99%-guaranteed solutions trading the remaining 1% of guarantee for performance. This paper aims at opening new directions to solve this problem, and we show that this result can be achieved through randomization.