Quick Adaptive Control of Optical Dynamic Systems with Neural Networks

Yang Huaijaing

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Quick Adaptive Control of Optical Dynamic Systems with Neural Networks

更新时间：2020-08-12

- Quick Adaptive Control of Optical Dynamic Systems with Neural Networks
- Optics and Precision Engineering Vol. 5, Issue 1, Pages: 22-27(1997)
- 作者机构：
  
  中国科学院长春光学精密机械研究所应用光学国家重点实验室长春,130022
- 作者简介：
- 基金信息：
- DOI：
  CLC：
- Received：26 December 1995，
  
  Published Online：15 February 1997，
  
  Published：15 February 1997
- 稿件说明：
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杨怀江. 混沌光学系统之快速神经网络自适应控制研究[J]. 光学精密工程, 1997,(1): 22-27

Yang Huaijaing. Quick Adaptive Control of Optical Dynamic Systems with Neural Networks[J]. Editorial Office of Optics and Precision Engineering, 1997,(1): 22-27
杨怀江. 混沌光学系统之快速神经网络自适应控制研究[J]. 光学精密工程, 1997,(1): 22-27 DOI：

Yang Huaijaing. Quick Adaptive Control of Optical Dynamic Systems with Neural Networks[J]. Editorial Office of Optics and Precision Engineering, 1997,(1): 22-27 DOI：

摘要

提出一种用于光动力学系统控制之快速神经网络自适应控制技术。该技术以一前向神经网络作为光动力学系统之系统辨识器

由其与光动力学系统之输出差值对系统控制参数进行调整以达到控制目的

由于神经网络系统辨识器在混沌加速BP算法的支持下可从光动力学系统输出时间序列进行快速动力学模型重构

因而此控制技术特别适用于对未知动力学表述的光动力学系统进行快速控制。文中成功地将此神经网络自适应控制技术应用于布喇格声光混沌系统进行的快速控制仿真实验中

Abstract

A quick adaptive algorithm for controlling the optical dynamic system

in which the system identifier of the controlled optical dynamic system is a feedforwad neural network

is presented in this paper.In this NN adaptive algorithm the difference between the outputs of the controlled optical dynamic system and the trained NN identifier is employed as the negative feedback in readjusting the systems's control parameter.Because the NN identifier can reconstruct the dynamic model of the controlled optical dynamic system quickly and precisely from the output time series with the support of the chaos speedup BP algorithm

this adaptive control algorithm is considered applied to control the otpical dynamic system when the reference model for control can not be obtained in advance.This improved NN adaptive control algorithm has been applied successfuly to control the Bragg diffraction acousto optic bistable system quickly in the computer simulation.

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Related Author

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Yang Huaijiang

Related Institution

School of Automation Engineering, Qingdao Technological University

School of Electrical Engineering, Shandong University

School of Control Science and Engineering, Shandong University

Department of Physics and Electronics, Taishan University

State Key Laboratory of Applied Optics, Changchun Institute of Optics and Fine Mechanics, Chinese Academy of Sciences

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