Control system for electric arc furnace
First Claim
1. In a control system for an electric arc furnace of a type having electrode means, drive means for changing a position of said electrode means, means for obtaining one or more furnace state measurements, means responsive to said furnace state measurements for establishing one or more state measurement set-points for optimizing operation of said furnace, and furnace regulator means responsive to said set-points and said furnace state measurements to use a selected control algorithm to dynamically calculate a change in electrode position for causing said furnace state measurements to more closely approach their respective set-points, and for causing said drive means to move said electrode means accordingly;
- the improvement wherein;
said regulator means includes means for establishing variable coefficients governing said selected control algorithm;
means for presenting said furnace state measurements and set-points and said variable coefficients as inputs to said regulator means;
said regulator means being arranged to calculate a regulator output as a function of said inputs representing said furnace state measurements, said input representing said set-points and said variable coefficients, and to present said regulator output to said drive means to control the position of said electrode means;
means for comparing said set-points and said regulator output for calculating a regulator error signal;
and means responsive to said regulator error signal for practically continuously modifying said variable coefficients accordingly.
2 Assignments
0 Petitions
Accused Products
Abstract
An improved arc furnace regulator employs neural circuits connected in a multi-layer network configuration with various weighted relationships between the successive layers which are automatically changed over time as a function of an error signal by means of the back-propagation method so that the regulator gradually improves its control algorithm as a result of accumulated experience. The network is implemented in software which can be developed and run on a PC with extra co-computing capability for greater execution speed. A second trainable neural network which emulates the arc furnace is used to develop the error signal, and is trained in mutually exclusive time periods with the training of the regular network.
67 Citations
30 Claims
-
1. In a control system for an electric arc furnace of a type having electrode means, drive means for changing a position of said electrode means, means for obtaining one or more furnace state measurements, means responsive to said furnace state measurements for establishing one or more state measurement set-points for optimizing operation of said furnace, and furnace regulator means responsive to said set-points and said furnace state measurements to use a selected control algorithm to dynamically calculate a change in electrode position for causing said furnace state measurements to more closely approach their respective set-points, and for causing said drive means to move said electrode means accordingly;
- the improvement wherein;
said regulator means includes means for establishing variable coefficients governing said selected control algorithm; means for presenting said furnace state measurements and set-points and said variable coefficients as inputs to said regulator means; said regulator means being arranged to calculate a regulator output as a function of said inputs representing said furnace state measurements, said input representing said set-points and said variable coefficients, and to present said regulator output to said drive means to control the position of said electrode means; means for comparing said set-points and said regulator output for calculating a regulator error signal; and means responsive to said regulator error signal for practically continuously modifying said variable coefficients accordingly.
- the improvement wherein;
-
2. In a control system for an electric arc furnace of a type having electrode means, drive means for changing a position of said electrode means, means for obtaining one or more furnace state measurements, means responsive to said furnace state measurements for establishing one or more state measurement set-points for optimizing operation of said furnace, and furnace regulator means responsive to said set-points and said furnace state measurements to calculate a change in electrode position for causing said furnace state measurements to more closely approach their respective set-points, and for causing said drive means to move said electrode means accordingly;
- the improvement wherein said regulator means comprises;
furnace regulator emulator neural network means having at least one layer and at least one input means, each said layer having at least one neural element, said furnace regulator emulator neural network means also having at least one coupling means for connecting each said neural element to at least one other said neural element or at least one said input means, each said coupling means having a regulator emulator changeable weight controlling a degree of coupling provided thereby; means for presenting inputs to said furnace regulator emulator neural network means representing said furnace state measurements and said set-points; said furnace regulator emulator neural network means being arranged to calculate a regulator output as a function of said inputs representing said furnace state measurements, said inputs representing said set-points and said regulator emulator changeable weight, and to present said regulator output to said drive means to control the position of said electrode means; means for comparing said set-points and said inputs representing said furnace state measurements for calculating a regulator error signal; and means responsive to said regulator error signal for practically continuously modifying said regulator emulator changeable weight accordingly. - View Dependent Claims (3, 4, 5, 6, 7)
- the improvement wherein said regulator means comprises;
-
8. A system for controlling a process, said system comprising:
-
process emulator means arranged to emulate said process; a regulator including trainable regulator neural network means arranged to regulate said process; means for establishing a desired state of said process and presenting said desired state to said regulator neural network means; said regulator neural network means outputting a process control signal to control said process; means for presenting said process control signal to said process emulator means; said process emulator means being arranged to calculate a simulated state of said process as a function of said process control signal; means for comparing said simulated state with said desired state to derive a process control error signal; and
means for training said regulator neural network means as a function of said process control error signal. - View Dependent Claims (9, 10)
-
-
11. A process control system comprising:
- at least two trainable neural networks, including a process emulator neural network arranged to emulate a process exhibiting a behavior and a regulator neural network arranged to regulate said process;
means for obtaining a measurement of a present state of said process and presenting said measurement of the present state of said process to said regulator neural network means; means for establishing a desired state of said process; said regulator neural network means being arranged to output a process control signal adapted to control said process; means for presenting the measurement of the present state of said process and said process control signal to said process emulator neural network means, said process emulator neural network means being arranged to calculate a simulated state of said process as a function of said process control signal; means for comparing said simulated state with said desired state to derive a process control error signal; means for training said regulator neural network means as a function of said process control error signal; means for providing a reference signal representing a state of said process and exemplary of the behavior of said process; means for comparing said reference signal with said simulated state to derive a process emulator error signal; and means for training said process emulator neural network means as a function of said process emulator error signal. - View Dependent Claims (12)
- at least two trainable neural networks, including a process emulator neural network arranged to emulate a process exhibiting a behavior and a regulator neural network arranged to regulate said process;
-
13. In a control system for a chaotic process employing at least one regulatable means, means for obtaining at least one present process state measurement, means for establishing at least one state measurement set-point for optimizing operation of said process, and regulator means responsive to said set-point and said present process state measurement to use a selected control algorithm to dynamically calculate a change in a condition of said regulatable means for causing said process state measurement to more closely approach said set-point, and for adjusting said regulatable means accordingly;
- the improvement wherein;
said regulator means includes means for establishing variable coefficients governing said selected control algorithm; means for presenting said present process state measurement, said coefficients, and said set-point inputs to said regulator means; said regulator means is arranged to calculate a regulator output as a function of said outputs representing said present process state measurement, said set-point and said coefficients, and to present said regulator output to adjust said regulatable means; means for comparing inputs representing said set-point and inputs representing said process state measurement for calculating a regulator error signal; and means responsive to said regulator error signal for practically continuously modifying said coefficients accordingly. - View Dependent Claims (14, 15, 16, 17, 18)
- the improvement wherein;
-
19. In a control system for an electric arc furnace of a type having electrode means, an alternating current power supply for said electrode means including a transformer having primary and secondary windings, drive means for changing the position of said electrode means, means for obtaining at least one present furnace state measurement, means responsive to said furnace state measurement for establishing at least one state measurement set-point for optimizing operation of said furnace, and furnace regulator means responsive to said set-point and said present furnace state measurement to use a selected control algorithm to dynamically calculate a change in electrode position for causing said furnace state measurement to more closely approach said set-point, and for causing said drive means to move said electrode means accordingly;
- the improvement wherein;
said furnace state measurement means includes means for deriving a measurement of the instantaneous voltage at said primary winding of said power supply transformer; and means for presenting inputs to said regulator means representing said set-point and said furnace state including at least said derived measurement of the instantaneous voltage at said primary winding; said regulator means being arranged to calculate a regulator output as a function of said inputs representing said furnace state inputs, and said set-point, and to present said regulator output to said drive means to control the position of said electrode means. - View Dependent Claims (20, 21, 22, 23, 24)
- the improvement wherein;
-
25. A system for controlling a process, said system comprising:
-
process emulator means arranged to emulate said process; a regulator including trainable regulator neural network means arranged to regulate said process; means for establishing a desired state of said process and presenting said desired state to said regulator neural network means; said regulator neural network means outputting a process control signal to control said process; means for presenting said process control signal to said process emulator means; said process emulator means being arranged to calculate a predicted future state of said process as a function of said process control signal; means for comparing said predicted future state with said desired state to derive a process control error signal; and means for training said regulator neural network means as a function of said process control error signal. - View Dependent Claims (26, 27, 28, 29, 30)
-
Specification