Variance-Constrained Multi-Objective Stochastic Control and Filtering (e-bog) af Bo, Yuming
Bo, Yuming (forfatter)

Variance-Constrained Multi-Objective Stochastic Control and Filtering e-bog

1276,86 DKK (ekskl. moms 1021,49 DKK)
Unifies existing and emerging concepts concerning multi-objective control and stochastic control with engineering-oriented phenomena Establishes a unified theoretical framework for control and filtering problems for a class of discrete-time nonlinear stochastic systems with consideration to performance Includes case studies of several nonlinear stochastic systems Investigates the phenomena of in…
Unifies existing and emerging concepts concerning multi-objective control and stochastic control with engineering-oriented phenomena Establishes a unified theoretical framework for control and filtering problems for a class of discrete-time nonlinear stochastic systems with consideration to performance Includes case studies of several nonlinear stochastic systems Investigates the phenomena of incomplete information, including missing/degraded measurements, actuator failures and sensor saturations Considers both time-invariant systems and time-varying systems Exploits newly developed techniques to handle the emerging mathematical and computational challenges
E-bog 1276,86 DKK
Forfattere Bo, Yuming (forfatter)
Forlag Wiley
Udgivet 27.04.2015
Genrer PBWL
Sprog English
Format epub
Beskyttelse LCP
ISBN 9781118929469
Unifies existing and emerging concepts concerning multi-objective control and stochastic control with engineering-oriented phenomena Establishes a unified theoretical framework for control and filtering problems for a class of discrete-time nonlinear stochastic systems with consideration to performance Includes case studies of several nonlinear stochastic systems Investigates the phenomena of incomplete information, including missing/degraded measurements, actuator failures and sensor saturations Considers both time-invariant systems and time-varying systems Exploits newly developed techniques to handle the emerging mathematical and computational challenges