Neurofuzzy modelling and control.
Electrotechnology, 6, (2), .
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An increase in the sophistication of control systems, both in terms of performance and flexibility is required if the current desire for autonomy and inherent inbuilt intelligence in manufacturing and manufactured goods is to be realised. These new control systems will have to deal with ill-defined complex dynamics and non-linear relationships over wide operating envelopes. Recent developments in neural networks and fuzzy logic present opportunities for a radical innovation in control system design and management. The developments have already provided improved product quality features, and even more importantly they have presented the opportunity to provide near optimal control of complex hierarchical multi-faceted processes in a coherent manner. They provide this opportunity through an intelligent integration of both quantitative and qualitative aspects of the problem to be addressed.
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