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A Fokker-Planck control framework for multidimensional stochastic processes. (English) Zbl 1251.35196
Summary: An efficient framework for the optimal control of probability density functions (PDFs) of multidimensional stochastic processes is presented. This framework is based on the Fokker-Planck equation that governs the time evolution of the PDF of stochastic processes and on tracking objectives of terminal configuration of the desired PDF. The corresponding optimization problems are formulated as a sequence of open-loop optimality systems in a receding-horizon control strategy. Many theoretical results concerning the forward and the optimal control problem are provided. In particular, it is shown that under appropriate assumptions the open-loop bilinear control function is unique. The resulting optimality system is discretized by the Chang-Cooper scheme that guarantees positivity of the forward solution. The effectiveness of the proposed computational framework is validated with a stochastic Lotka-Volterra model and a noised limit cycle model.

MSC:
35R60 PDEs with randomness, stochastic partial differential equations
35Q84 Fokker-Planck equations
35K57 Reaction-diffusion equations
60H25 Random operators and equations (aspects of stochastic analysis)
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