Stochastic and adaptive control theory; estimation, identification and decision theory; computer control; system design; Kalman filters.
Dr. Kalata`s current research interests are in the area of stochastic and adaptive control theory; estimation, identification and decision theory; computer control and system design.
His current projects involve real-time control of stochastic processes which not only involve implementation of Kalman Filters but also adaptive strategies for self-tuning and disturbance accommodation.
*Real-time Control of Stochastic Systems: Real-time hardware control systems inherently have disturbances which require not only noise filtering but also disturbances accommodation control strategies in which the disturbances must be identified, filtered and accommodated. The stochastic control algorithms are implemented via real-time computer control systems.
*Practical Implementation of Kalman Filters: Kalman Filtering Theory has been one of the most revolutionary additions to Control Theory. However, its complexity increases as the noise processes become biased, colored and correlated. This research investigation involves restructuring the filtering problem thereby removing the algorithm complexity and leads to the simplest form of the Kalman Filter which can be used in a wide class of filtering problems.