System and method for nonlinear dynamic control based on soft computing with discrete constraints

A technology of control systems and controllers, applied in general control systems, control/regulation systems, calculations, etc.

Inactive Publication Date: 2005-09-21
YAMAHA MOTOR CO LTD
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

State-of-the-art control systems based on soft computing with genetic analyzers are not necessarily well suited to equipment that must be changed or controlled in a step-by-step manner, partly due to the operation of genetic analyzers

Method used

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  • System and method for nonlinear dynamic control based on soft computing with discrete constraints
  • System and method for nonlinear dynamic control based on soft computing with discrete constraints
  • System and method for nonlinear dynamic control based on soft computing with discrete constraints

Examples

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Embodiment Construction

[0060] figure 1 is a block diagram of a control system 100 for controlling equipment based on soft computing. Within the controller 100 a reference signal y is provided to a first input of an adder 105 . The output of the adder 105 is an error signal ε, which is provided to the input of the fuzzy controller (FC) 143 and the input of the proportional-integral-derivative (PID) controller 150 . The output of the PID controller 150 is the control signal u * , the control signal is provided to the control input of the device 120 and to the first input of the entropy calculation module 132 . Disturbance m(t) 110 is also provided to the input of device 120 . The output of the device 120 is the response x, which is provided to a second input of the entropy calculation module 132 and to a second input of the adder 105 . The second input of adder 105 is negated such that the output of adder 105 (the error signal) is the value of the first input minus the value of the second input. ...

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Abstract

A control system using a genetic analyzer based on discrete constraints is described. In one embodiment, a genetic algorithm with step-coded chromosomes is used to develop a teaching signal that provides good control qualities for a controller with discrete constraints, such as, for example, a step-constrained controller. In one embodiment, the control system uses a fitness (performance) function that is based on the physical laws of minimum entropy. In one embodiment, the genetic analyzer is used in an off-line mode to develop a teaching signal for a fuzzy logic classifier system that develops a knowledge base. The teaching signal can be approximated online by a fuzzy controller that operates using knowledge from the knowledge base. The control system can be used to control complex plants described by nonlinear, unstable, dissipative models. In one embodiment, the step-constrained control system is configured to control stepping motors.

Description

technical field [0001] The present invention relates generally to nonlinear electronic control system optimization. Background technique [0002] Feedback control systems are widely used to maintain the output of a dynamic system at a desired value, although external disturbances may cause the output to deviate from the desired value. For example, a domestic space heater controlled by a thermostat is an example of a feedback control system. The thermostat constantly measures the temperature of the air inside the room, and when the temperature falls below a desired minimum temperature, the thermostat turns on the furnace. When the internal temperature reaches the desired minimum temperature, the thermostat turns off the furnace. The thermostat-furnace system maintains the temperature in the room at a substantially constant value regardless of external disturbances, such as a decrease in the outside temperature. A similar type of feedback control is used in many application...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06F19/00G05B13/02G05B13/04G06N3/00
CPCG05B13/0285
Inventor 谢尔盖·V·乌里扬诺夫谢尔盖·潘菲洛夫高桥一树
Owner YAMAHA MOTOR CO LTD
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