Control method and apparatus using two neural networks
First Claim
1. A control method of controlling a controlled system, comprising:
- the first step of inputting current and future target controlled variables to a first neural network model and causing the first neural network model to execute a forward calculation to output a virtual manipulated variable initial value;
the second step of causing a second neural network model to receive the virtual manipulated variable initial value obtained in the first step as a virtual manipulated variable and a controlled variable obtained from said controlled system at a current time, and causing the second neural network model to execute a forward calculation to output a predicted controlled variable;
the third step of obtaining an error of the predicted controlled variable obtained in the second step with respect to the future target controlled variable;
the fourth step of obtaining a correction amount for the virtual manipulated variable in accordance with a back propagation calculation of said second neural network model, using the error obtained in the third step, thereby correcting the virtual manipulated variable in accordance with the correction amount;
the fifth step of outputting the virtual manipulated variable corrected in the fourth step to the controlled system as a manipulated variable; and
the sixth step of causing the first neural network model to perform learning in an error back propagation learning method, using as a teacher signal the virtual manipulated variable output to the controlled system.
1 Assignment
0 Petitions
Accused Products
Abstract
A control method of controlling a controlled system according to the invention comprises the first step of inputting a current and future target controlled variable to a first neural network model which performs learning using a past target controlled variable for the controlled system as an input signal and a past manipulated variable as a teacher signal, thereby obtaining a current virtual manipulated variable, the second step of causing a second neural network model, which have learnt to predict a behavior of the controlled system, to receive the virtual manipulated variable obtained in the first step and a controlled variable obtained from the controlled system at a current time, thereby obtaining a predicted controlled variable, the third step of obtaining an error of the predicted controlled variable obtained in the second step with respect to the target controlled variable, the fourth step of obtaining a correction amount for the virtual manipulated variable in accordance with a back propagation calculation of the second neural network model, using the error obtained in the third step, thereby correcting the virtual manipulated variable with the correction amount, and the fifth step of outputting the virtual manipulated variable corrected in the fourth step to the controlled system.
17 Citations
16 Claims
-
1. A control method of controlling a controlled system, comprising:
-
the first step of inputting current and future target controlled variables to a first neural network model and causing the first neural network model to execute a forward calculation to output a virtual manipulated variable initial value; the second step of causing a second neural network model to receive the virtual manipulated variable initial value obtained in the first step as a virtual manipulated variable and a controlled variable obtained from said controlled system at a current time, and causing the second neural network model to execute a forward calculation to output a predicted controlled variable; the third step of obtaining an error of the predicted controlled variable obtained in the second step with respect to the future target controlled variable; the fourth step of obtaining a correction amount for the virtual manipulated variable in accordance with a back propagation calculation of said second neural network model, using the error obtained in the third step, thereby correcting the virtual manipulated variable in accordance with the correction amount; the fifth step of outputting the virtual manipulated variable corrected in the fourth step to the controlled system as a manipulated variable; and the sixth step of causing the first neural network model to perform learning in an error back propagation learning method, using as a teacher signal the virtual manipulated variable output to the controlled system. - View Dependent Claims (2, 3, 4)
-
-
5. A control method of controlling a controlled system, comprising:
-
the first step of providing a second neural network model having learnt to predict a behavior of the controlled system; the second step of inputting current and future target controlled variables to a first neural network model and causing the first neural network model to execute a forward calculation to output a virtual manipulated variable initial value; the third step of causing the second neural network model to receive the virtual manipulated variable initial value obtained in the first step as a virtual manipulated variable and a controlled variable obtained from said controlled system at a current time, and causing the second neural network model to execute a forward calculation to output a predicted controlled variable; the fourth step of obtaining an error of the predicted controlled variable obtained in the third step with respect to the future target controlled variable; the fifth step of obtaining a correction amount for the virtual manipulated variable in accordance with a back propagation calculation of said second neural network model, using the error obtained in the fourth step, thereby correcting the virtual manipulated variable with the correction amount; the sixth step of outputting the virtual manipulated variable corrected in the fifth step to the controlled system as a manipulated variable; and the seventh step of causing the first neural network model to perform learning in an error back propagation learning method, using as a teacher signal the virtual manipulated variable output to the controlled system. - View Dependent Claims (6, 7, 8)
-
-
9. A control apparatus for controlling a controlled system, comprising:
-
a first neural network model for receiving current and future target controlled variables to obtain a current virtual manipulated variable initial value; a second neural network model for receiving a current controlled variable obtained from the controlled system and a virtual manipulated variable whose initial value is the virtual manipulated variable initial value obtained from the first neural network model, for outputting a predicted controlled variable, and for calculating a correction amount for the virtual manipulated variable by executing an error back propagation calculation on the basis of an error between the predicted controlled variable and the future target controlled variable; and means for correcting the virtual manipulated variable using the correction amount and the virtual manipulated variable and outputting the corrected virtual manipulated variable to the controlled system. - View Dependent Claims (10, 11, 12, 13, 14, 15, 16)
-
Specification