This is the first book to systematically present control theory for stochastic distributed parameter systems, a comparatively new branch of mathematical control theory. The new phenomena and difficulties arising in the study of controllability and optimal control problems for th…
"This book copes with the filter design, fault estimation and reliable control problems for different classes of nonlinear stochastic time-varying systems with network-enhanced complexities. Divided into three parts, first one discusses the finite-horizon filtering, fault estima…
"This book copes with the filter design, fault estimation and reliable control problems for different classes of nonlinear stochastic time-varying systems with network-enhanced complexities. Divided into three parts, first one discusses the finite-horizon filtering, fault estima…
"This book copes with the filter design, fault estimation and reliable control problems for different classes of nonlinear stochastic time-varying systems with network-enhanced complexities. Divided into three parts, first one discusses the finite-horizon filtering, fault estima…
"The inverse problem of identifying random parameters and random initial/boundary conditions in stochastic partial differential equations is a vibrant and emerging research domain that has found numerous applications. Another related problem that also of paramount importance is …
"The inverse problem of identifying random parameters and random initial/boundary conditions in stochastic partial differential equations is a vibrant and emerging research domain that has found numerous applications. Another related problem that also of paramount importance is …
"The inverse problem of identifying random parameters and random initial/boundary conditions in stochastic partial differential equations is a vibrant and emerging research domain that has found numerous applications. Another related problem that also of paramount importance is …
"The inverse problem of identifying random parameters and random initial/boundary conditions in stochastic partial differential equations is a vibrant and emerging research domain that has found numerous applications. Another related problem that also of paramount importance is …
This book concerns continuous-time controlled Markov chains, also known as continuous-time Markov decision processes. They form a class of stochastic control problems in which a single decision-maker wishes to optimize a given objective function. This book is also concerned with…
Model Predictive Control describes the development of tractable algorithms for uncertain, stochastic, constrained systems. The starting point is classical predictive control and the appropriate formulation of performance objectives and constraints to provide guarantees of closed…
Stochastic Numerical Methods introduces at Master level the numerical methods that use probability or stochastic concepts to analyze random processes. The book aims at being rather general and is addressed at students of natural sciences (Physics, Chemistry, Mathematics, Biology…
Stochastic Numerical Methods introduces at Master level the numerical methods that use probability or stochastic concepts to analyze random processes. The book aims at being rather general and is addressed at students of natural sciences (Physics, Chemistry, Mathematics, Biology…
