Neuromorphic pitch attitude regulation of an underwater telerobot

The experimental results of using trained neural networks to regulate the pitch attitude of an underwater telerobot are presented. The neuromorphic control algorithm developed for teaching the networks is a direct application of the back-propagation entrainment method, with those modifications required to pose the problem in a control systems framework. The networks perform in the field as predicted by simulation results; however, it is observed that the complexity of the calculations required can create unacceptable delays when using a single serial microprocessor to compute the control. This problem becomes especially acute when scaling the architecture to more complex neural topologies. Special-purpose hardware, which directly implements the neural equations and, hence, realizes the benefits of the natural parallelism of these models, is seen as a necessary development for the effective use of neural controllers.<
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