Neural network extreme control method and system based on chaos annealing and parameter destabilization

A parameter disturbance, neural network technology, applied in general control system, control/regulation system, adaptive control and other directions, to achieve the effect of saving production mode and saving energy

Inactive Publication Date: 2009-04-15
NAVAL AERONAUTICAL & ASTRONAUTICAL UNIV PLA
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  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0005] In order to overcome the defects of existing extreme value control methods, the present invention provides a neural network extreme value control method and system based on chaotic annealing and parameter perturbation

Method used

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  • Neural network extreme control method and system based on chaos annealing and parameter destabilization
  • Neural network extreme control method and system based on chaos annealing and parameter destabilization
  • Neural network extreme control method and system based on chaos annealing and parameter destabilization

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Embodiment 2

[0113] Adopt the model emulation mode of the system of the present invention to complete the extreme value control task to the third-order extreme value search system with Branin output function, the model description of this extreme value search system is:

[0114] x · 1 = x 1 + x 2 + 0.3 x 3 + u 1

[0115] x · 2 = 0.5 x 1 + 2 x 2 + 1.5 x 3 + u 2 - - - ( 28 ...

Embodiment 3

[0122] The model simulation mode of the system of the present invention is adopted to complete the extreme value control task of a nonlinear fourth-order extreme value search system with a Six-Hump Camel-Back output function. The model description of this extreme value search system is:

[0123] x · 1 = x 1 + 5 x 2 + 0.3 x 3 - x 4 + 0.5 u 1

[0124] x · 2 = 0.5 x 1 + 2 x 2 + 1.5 sin ( ...

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Abstract

The invention provides a neutral network extreme value control method based on chaotic annealing and parameter perturbation, and a system thereof. The control method transforms a control problem of an extreme value search system to solve an extreme value point problem with zero rate of slope in an output function of a controlled system. According to the extreme value point solving problem, a pair of dual problems with constraint conditions are constructed. A neutral network solving dual problem based on chaotic annealing and parameter perturbation is established, which comprises a chaotic annealing initial search phase, a parameter perturbation middle search phase and a final search phase of a natural network. The global optimum search variable can be obtained by the solving of the neutral network extreme value control method. According to the obtained global optimum search variable, the output value of the extreme value search system is driven to converge to a global extreme value point of the output function, thus realizing the control purpose of the extreme value search system. The control system provided by the invention is divided into a module simulation mode and a real time control mode and realizes the application of the control method in the extreme value search system respectively from two aspects of off-line module simulation and real time system control.

Description

technical field [0001] The present invention relates to the technical field of artificial intelligence control, more specifically, the present invention relates to a neural network extreme value control method and system based on chaotic annealing and parameter perturbation. Background technique [0002] Extremum Seeking System (Ext remum Seeking System) is a kind of practical system that widely exists in the production and life of the public, industrial control and military applications, such as the control system of the jet engine combustion chamber of the gas turbine, the brake control of automobiles and aircraft Systems, tight formation flight control of aircraft, tubular reactor control systems, and human exercise machine control systems all fall under the category of extremum search systems. In many practical extremum search systems, the reference trajectory between the system's reference input and output is difficult to be accurately known by the designer, and due to ...

Claims

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Application Information

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IPC IPC(8): G05B13/02
Inventor 胡云安左斌李静
Owner NAVAL AERONAUTICAL & ASTRONAUTICAL UNIV PLA
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