Generation of a control system for a target system
AssigneeCurious AI Oy
InventorsHarri VALPOLA, Eva KOPPALI
Life of this patent
Estimating the term…
Abstract
The invention relates to a method for generating a control system for a target system, wherein: operational data is received; a first neural model component is trained with the received operational data for generating a prediction on a state of the target system based on the received operational data; a second neural model component is trained with the operational data for generating a regularizer for use in inverting the first neural model component; and the control system is generated by inverting the first neural model component by optimization and arranging to apply the regularizer generated with the second neural model component in the optimization. The invention relates also to a system and a computer program product.
Claims18
A method for generating a control system for a target system, the method comprising:
- receiving operational data of at least one source system,
- training a first neural model component of a neural network with the received operational data, wherein the first neural model component is trained to generate a prediction on a state of the target system based on the received operational data,
- training a second neural model component of the neural network with the operational data, wherein the second neural model component is trained to generate a regularizer for use in inverting the first neural model component, and
- generating the control system for the target system by inverting the first neural model component by optimization and arranging to apply the regularizer generated with the second neural model component in the optimization.
A control system for a target system, the control system comprising at least one neural network, wherein the control system is configured to be generated by:
- receiving operational data of at least one source system,
- training a first neural model component of the neural network with the received operational data, wherein the first neural model component is trained to generate a prediction on a state of the target system based on the received operational data in response to an input signal,
- training a second neural model component of the neural network with the operational data, wherein the second neural model component is trained to generate a regularizer for use in inverting the first neural model component, and
- generating the control system for the target system by inverting the first neural model component by optimization and arranging to apply the regularizer generated with the second neural model component in the optimization.
A non-transitory computer program product comprising at least one computer-readable media having computer-executable program code instructions stored therein, for generating a control system for a target system, wherein the computer-executable program code instructions when executed on a computer cause the computer to:
- receive operational data of at least one source system,
- train a first neural model component of a neural network with the received operational data, wherein the first neural model component is trained to generate a prediction on a state of the target system based on the received operational data,
- train a second neural model component of the neural network with the operational data, wherein the second neural model component is trained to generate a regularizer for use in inverting the first neural model component, and
- generate the control system for the target system by inverting the first neural model component by optimization and arranging to apply the regularizer generated with the second neural model component in the optimization.
Dependencies are inferred from the claim text.