Sparsity-Constrained Linear Dynamical Systems

This volume provides a comprehensive overview of recent research advances in the upcoming field of sparse control and state estimation of linear dynamical systems. The contents offer a detailed introduction to the subject by combining classical control theory and compressed sensing. It covers conceptual foundations, including the formulation, theory, and algorithms, and outlines numerous remaining research challenges. Specifically, the book provides a detailed discussion on observability, controllability, and stabilizability under sparsity constraints. It also presents efficient, systematic, and rigorous approaches to estimating the sparse initial states and designing sparse control inputs. It also gives background materials fromrealanalysis and probability theory and includes applications in network control, wireless communication, and image processing.Itserves asacompendioussource for graduate students and researchers in signal processing and control systems toacquire a thorough understanding ofthe underlying unified themes.The academic and industrial professionals working onthe design and optimization ofsparsity-constrained systems also benefit fromthe exposureto the array of recent works on linear dynamical systems and related mathematical machinery.