Global and local optimization in adaptive neurocontrol

Global optimization algorithms are more adequate for neurocontrol applications than presently used local algorithms. If embedded in an appropriate scheme providing for training data accumulation, they can be used also for online adaptation. The results of a computational experiment show that the danger of divergence of adaptation with help of local algorithms is not only theoretical-it is significant also for relatively simple plants