Control method using neural networks and a voltage/reactive-power controller for a power system using the control method

• US 5,485,545 A
• Filed: 08/26/1994
• Issued: 01/16/1996
• Est. Priority Date: 06/20/1991
• Status: Expired due to Fees

• Current Assignee: Mitsubishi Denki Kabushiki Kaisha (Mitsubishi Electric Corporation)
• Original Assignee: Mitsubishi Denki Kabushiki Kaisha (Mitsubishi Electric Corporation)
• Inventors: Kojima, Yasuhiro, Izui, Yoshio, Goda, Tadahiro, Kyomoto, Sumie
• Primary Examiner(s): Downs, Robert W.
• Application Number:
  US08/295,072
• Time in Patent Office: 508 Days
• Field of Search: 395/21, 395/22, 395/23, 395/24
• US Class Current: 706/23
• CPC Class Codes: G05B 13/027 using neural networks only
• CPC Class Codes: H02J 3/18 Arrangements for adjusting, eliminating or compensating reactive power in networks for adjustment of voltage H02J3/16
• CPC Class Codes: Y02E 40/30 Reactive power compensation

Abstract

A neural network apparatus and method for use in applications such as in a voltage/reactive-power controller in which a neuro control-object simulator and a neuro controller pre-learn so as to make input-output relations of the controller match the input-output relations of a control unit and so as to make input-output relations of the simulator match input-output relations of a control object. The controller re-learns so as to make the output of the simulator match an input corresponding to a desired output of the control object. After re-learning, the controller controls the control-object.

Claims

1. A control method for controlling a control object by means of a neuro controller made up of a recurrent neural network, said control method comprising the steps of:

connecting said neuro controller in parallel to a control unit having functions for controlling said control object and connecting in parallel to said control object a neuro control-object simulator made up of a recurrent neural network for simulating said control object;

operating said neural network of said neuro controller and a neural network making up said neuro control-object simulator to perform a pre-learning phase so as to make input-output relations of said neuro controller match input-output relations of said control unit, and so as to make in said pre-learning phase input-output relations of said neuro control-object simulator match input-output relations of said control object;

connecting the output and the input of said neuro controller to the input and the output, respectively of said neuro control-object simulator;

operating said neural network of said neuro controller to perform a re-learning phase so as to make the output of said neuro control-object simulator match the input of said neuro controller; and

thereafter connecting said neuro controller to control said control object after completing said re-learning phase and thereafter controlling said control object using only said neuro controller.

2. A control method according to claim 1, further comprising a step of comparing the output of said control object to the output of said neuro control-object simulator after said re-learning phase and causing said neuro controller and said neuro control-object simulator go through a second re-learning phase if the difference between said outputs exceeds a predetermined value.

3. A voltage/reactive power controller for controlling voltages and reactive power of a power system comprising:

a voltage/reactive-power control unit having functions for controlling a power system;

a neuro control-object simulator made up of a first recurrent neural network, wherein said first recurrent neural network has undergone a pre-learning process so as to make input-output relations of said neuro control-object simulator match input-output relations of said power system; and

a neuro controller made up of a second recurrent neural network, wherein said second recurrent neural network has undergone a pre-learning process so as to make input-output relations of said second recurrent neural network match input-output relations of said voltage/reactive-power control unit and has further undergone a re-learning process so as to make the output of said neuro control-object simulator match the input of said neuro controller,

said power system being connected to be controlled only by said neuro controller after said pre-learning and re-learning processes have been completed.

4. A voltage/reactive-power controller according to claim 3, wherein said voltage/reactive-power control unit has a power pattern approximating characteristics of a power system and controls said power system based on said pattern.

5. A voltage/reactive-power controller according to claim 3, wherein said neuro control-object simulator receives control signals from said neuro controller even after said learning processes have been completed and a monitor is further incorporated therein for comparing the output of said power system to the output of said neuro control-object simulator and for issuing a request to said neuro controller to undergo a re-learning process if the difference between said outputs exceeds a predetermined value.

6. A voltage/reactive-power controller according to claim 3, further including a deciding unit for keeping track of control signals of said neuro controller and altering connections so that said power system is controlled by said control unit if any of said control signals exceeds a predetermined value.