Neural network predictive control cost function designer
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United States of America Patent
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Nov 4, 2008
Grant Date -
Mar 3, 2005
app pub date -
Aug 28, 2003
filing date -
Aug 28, 2003
priority date (Note) -
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status (Latency Note)
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Abstract
A method, a computer-readable medium, and a system for tuning a cost function to control an operational plant are provided. A plurality of cost function parameters is selected. Predicted future states generated by the neural network model are selectively incorporated into the cost function, and an input weight is applied to a control input signal. A series of known signals are iteratively applied as control input inputs, and the cost output is calculated. A phase is taken of the control and plant outputs in response to each of the known signals and combined, thereby allowing effective combinations of the cost function parameters, the input weight, and the predicted future states to be identified.
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