US 11,443,219 B2 · Model estimation system, method, and program

Abstract

A model estimation system estimates a model of a system represented by an ordinary differential equation with all coefficients being non-zero, and with which input data and a state at each time can be obtained. When an order of the ordinary differential equation and input data and a state at multiple past times in the system are inputted, a model expression construction unit constructs an expression representing a model by using a first matrix that is a matrix according to the order and has only some elements as unknown elements and a second matrix that is a matrix according to the order and has only some one element as an unknown element. A model estimation unit uses input data and a state at multiple past times, to estimate the model by learning unknown elements of the first matrix and the unknown element of the second matrix.

Claims6

Dependent claims

A model estimation system for estimating a model of a system that is represented by an ordinary differential equation with all coefficients being non-zero and allows input data and a state at each time to be obtained, the model estimation system comprising:

at least one memory configured to store program instructions;
at least one processor configured to execute the program instructions to implement:
a model expression construction unit which constructs an expression representing a model for predicting a state of the system at a next time from input data and a state of the system at one time, when an order of the ordinary differential equation and input data and a state at multiple past times in the system are inputted, by using a first matrix that is a matrix according to the order and has only some elements as unknown elements and a second matrix that is a matrix according to the order and has only one element as an unknown element;
a model estimation unit which estimates the model by machine learning unknown elements of the first matrix and an unknown element of the second matrix in the expression by using input data and a state at the multiple past times;
and
a model implementing unit which implements controllability of a target system based on transition from an initial state to a target state of the estimated model.

3 more elements

A model estimation method for estimating a model of a system that is represented by an ordinary differential equation with all coefficients being non-zero and allows input data and a state at each time to be obtained, wherein

a computer
constructs an expression representing a model for predicting a state of the system at a next time from input data and a state of the system at one time, when an order of the ordinary differential equation and input data and a state at multiple past times in the system are inputted, by using a first matrix that is a matrix according to the order and has only some elements as unknown elements and a second matrix that is a matrix according to the order and has only one element as an unknown element;
and
estimates the model by machine learning unknown elements of the first matrix and the unknown element of the second matrix in the expression by using input data and a state at the multiple past times;
and
implements controllability of a target system based on transition from an initial state to a target state of the estimated model.

3 more elements

A non-transitory computer-readable recording medium in which a model estimation program is recorded, the model estimation program causing a computer to estimate a model of a system that is represented by an ordinary differential equation with all coefficients being non-zero and allows input data and a state at each time to be obtained, the model estimation program causes

the computer to execute:
a model expression construction process of constructing an expression representing a model for predicting a state of the system at a next time from input data and a state of the system at one time, when an order of the ordinary differential equation and input data and a state at multiple past times in the system are inputted, by using a first matrix that is a matrix according to the order and has only some elements as unknown elements and a second matrix that is a matrix according to the order and has only one element as an unknown element;
a model estimation process of estimating the model by learning unknown elements of the first matrix and the unknown element of the second matrix in the expression by using input data and a state at the multiple past times;
and
an implementation process of implementing controllability of a target system based on transition from an initial state to a target state of the estimated model.

2 more elements

Dependencies are inferred from the claim text.

Model estimation system, method, and program

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Model estimation system, method, and program

Life of this patent

Abstract

Claims6