Method and apparatus for analyzing a neural network within...

G - Physics – 05 – B

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G05B 13/02 (2006.01)

Patent

CA 2157198

A distributed control system (14) receives on the input thereof the control inputs and then outputs control signals to a plant (10) for the operation thereof. The mea- sured variables of the plant and the control inputs are input to a pre- dictive model (34) that operates in conjunction with an inverse model (36) to generate predicted control inputs. The predicted control in- puts are processed through a filter (46) to apply hard constraints, the values of which are received from a control parameter block (22). Dur- ing operation, predetermined crite- rion stored in the control parame- ter block (22) are utilized by a cost minimization block (42) to gener- ate an error control signal which is minimized by the inverse model (36) to generate the control signals. The system works in two modes, an analyze mode and a runtime mode. In the analyze mode, the predictive model (34) and the inverse model (36) are connected to either training data or simulated data from the analyzer (30) and the operation of the plant (10) evaluated. The values of the hard constraints in filter (46) and the criterion utilized for the cost minimization (42) can then be varied to change the constraints on the control signals input to the control network, the predicted output of the predictive model (34) and the hard constraints stored in the filter (46). Cost coefficients can be utilized as the criterion to set the input values in accordance with predetermined cost constraints.

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