Optimal feedback control of robots in the case of random initial conditions

The aim of this paper is to construct an optimal feedback controller for robots, which takes into account stochastic uncertainties in the initial conditions.The method works with expected cost functions evaluating the primary control expenses and the tracking error. Furthermore, the free regulator parameters are selected then such that the expected total costs are minimized.Using stochastic optimization methods, random parameter variations are incorporated into the optimal control process. Hence, robust optimal feedback controls are obtained.At the end an example will be shown and a comparison to a standard PD-controller will be done.