Graduate-level text provides introduction to optimal control theory for stochastic systems, emphasizing application of basic concepts to real problems.

A bottom-up approach that enables readers to master and apply the latest techniques in state estimation This book offers the best mathematical approaches to est

A focused presentation of how sparse optimization methods can be used to solve optimal control and estimation problems.

Upper-level undergraduate text introduces aspects of optimal control theory: dynamic programming, Pontryagin's minimum principle, and numerical techniques for t

Recent developments in constrained control and estimation have created a need for this comprehensive introduction to the underlying fundamental principles. Thes