Quasi-Monte Carlo Methods in Robust Control Design

Many practical control problems are so complex that traditional analysis and design methods fail to solve. Consequently, in recent years probabilistic methods that provide approximate solutions to such ’difficult’ problems have emerged. Unfortunately, the uniform random sampling process usually used in such techniques unavoidably leads to clustering of the sampled points in higher dimensions. In this paper we adopt the quasi-Monte Carlo methods of sampling to generate deterministic samples adequately dispersed in the sample-space. Such approaches have shown to provide faster solutions than probabilistic methods in fields such as Financial Mathematics.