Neural network for constrained predictive control

Presents the way in which optimization neural nets can be used to implement generalized predictive control for systems with constrained inputs and outputs. A set of recursive formulas to obtain the net parameters from the process parameters for first-order systems is given. The results obtained by simulation and electronic implementation of the neural net are presented.<
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