Variance-Constrained Multi-Objective Stochastic Control and Filtering

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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