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Statistics-Based Approaches To Stochastic Optimal Control Problems, Aihong Wen

Industrial, Manufacturing, and Systems Engineering Dissertations

This dissertation develops practical approaches to stochastic optimal control problems in the absence of linear system transition functions, quadratic cost functions, and/or Gaussian random disturbances. In such type of problems, an analytical solution is impossible and numerical synthesis techniques have to be applied. The ''classic'' algorithms existing in the literature suffer from the problem of the''curse of dimensionality,'' an exponential increase of computation time and memory requirements as the dimension of the problem grows. The statistics-based numerical approaches are presented as the main tools for mitigating the ``curse of dimensionality'' phenomenon. Two approaches are explored: (A) stochastic dynamic programming (SDP), …