Abstract
AbstractA new control algorithm is developed for the discrete time, finite horizon adaptive LQG problem. In the new algorithm, randomization over linear control functions is performed at future stages to find a deterministic desired control U(k) at the current stage. This randomized linear control policy, which is U(k)‐dependent and non‐linear in measurements, incorporates explicitly the knowledge available about the unknown parameter at future stages in terms of the posterior distribution. At the same time it enables us to obtain a closed form expression of an approximation of the optimal control‐cost function. Numerical examples comparing the new solution with the optimal are also provided.
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