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Artificial neural networks possess several properties that make them particularly attractive for applications to modelling and control of complex non-linear systems. Topics include non-linear system identification, neural optimal control, top-down model based neural control design and stability analysis of neural control systems.
Modern industrial processes and systems require adaptable advanced control protocols able to deal with circumstances demanding "judgement" rather than simple "yes/no", "on/off" responses: circumstances where a linguistic description is often more relevant than a cut-and-dried numerical one.
Artificial neural networks possess several properties that make them particularly attractive for applications to modelling and control of complex non-linear systems. Topics include non-linear system identification, neural optimal control, top-down model based neural control design and stability analysis of neural control systems.
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