ITTC Project

Stochastic Adaptive Control and Related Topics

Project Award Date: 07-01-1999


The intent of this research is to investigate a variety of control stochastic problems. Typically to solve an adaptive control problem, it is necessary to identify the unknown parameter of the system and simultaneously to construct a control. The cost functional for the control problems is typically ergodic (average cost per unit time). A family of processes seems to have wide applicability. Adaptive control for stochastic distributed parameter systems is proposed by considering partially known semilinear systems. This family of systems includes some stochastic partial differential equations. The adaptive control of continuous time branching processes is proposed for investigation because these processes are important and little use of control has been made for these processes. Risk sensitive control problems are especially useful for financial models. This research work studies adaptive control for these problems. Results of this research should be applicable to physical systems that have stochastic models that are controlled and should enhance the understanding of these physical systems.


Faculty Investigator(s): Tyrone Duncan (PI), Bozenna Pasik-Duncan

Project Sponsors

Primary Sponsor(s): NSF

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