Demand for Randomized Algorithms for Analysis and Control of Uncertain Systems comes from control engineers who wish to apply more workable methods to a variety of uncertainties and from engineers who need a path between the demands of robust control and the unnecessary complications of optimal control. This book talks about these systems.
Moving on from earlier stochastic and robust control paradigms, this book introduces the reader to the fundamentals of probabilistic methods in the analysis and design of uncertain systems. It significantly reduces the computational cost of high-quality control and the complexity of the algorithms involved.
