Angielski
Variance-Constrained Multi-Objective Stochastic Control and Filtering establishes a unified framework for filtering and control problems for various discrete-time nonlinear stochastic systems with engineering-oriented complications such as parameter uncertainties, missing measurements, sensor/actuator faults and degraded outputs, which are typical phenomena resulting from the complexity in nowadays complex systems. Multiple performance requirements are simultaneously considered, which include the regional stability, steady-state variance, robustness, disturbance rejection attenuation, integrity against missing measurements, reliability against sensor/actuator failures, dissipativity and energy constraint. A set of latest techniques are covered to handle the emerging mathematical/computational challenges involved. This book covers this developing area of control and filtering theories for stochastic systems with multiple objective and variance constraints typically resulting from complex environments.
