A Sample-Wise Data Driven Control Solver for the Stochastic Optimal Control Problem with Unknown Model Parameters

In this work, an efficient sample-wise data driven control solver will be de-veloped to solve the stochastic optimal control problem with unknown model param-eters. A direct filter method will be applied as an online parameter estimation method that dynamically estimates the target model parameters upon receiving the data, and a sample-wise optimal control solver will be provided to efficiently search for the op-timal control. Then, an effective overarching algorithm will be introduced to combine the parameter estimator and the optimal control solver. Numerical experiments will be carried out to demonstrate the effectiveness and the efficiency of the sample-wise data driven control method.