A learning approach to the parameter-adaptive self-organizing control problem

A new algorithm for the solution of the Parameter-Adaptive Self-Organizing Control Problem is proposed. The algorithm is based on the learning property of the a posteriori probabilities of the parameter estimates, which forces the algorithm to converge to the optimal solution rapidly. The new algorithm is relatively simple to implement and does not consume extensive computer time. Comparison with existing algorithms is also given.