NEURAL NETWORKS IN PROCESS CONTROL - A SURVEY

Neural networks have become recently the focus of considerable attention in many disciplines, including process control where they can be used to solve highly nonlinear control problems. Feedforward neural networks have been the most widely applied for modelling and control purposes. This paper reviews both the fundamentals of feedforward neural networks and their use for the identification of the dynamics and the inverse dynamics of physical processes. Various control strategies based on the plant and plant inverse neural models, with and without adaptation, are presented. Finally, the performance of some control strategies are evaluated with a simple illustrative example.

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