Fuzzy neural networks for control of uncertain systems with time delays

This paper addresses the problem of control of the uncertain systems with time delays. Using fuzzy logic control and artificial neural network methodologies, the paper presents a self-learning fuzzy neural control scheme for general uncertain processes. In this scheme, a neural network compensator is designed instead of the classical Smith predictor for attenuating the adverse effects of time delays of the uncertain systems. The scheme has been used in control of welding pool dynamics of an arc welding process, experimental results show the control scheme to be viable.