Imaging Components, Systems, and Processing

Identification of electro-optical tracking systems using genetic algorithms and nonlinear resistance torque

[+] Author Affiliations
Yixiang Lin

Wuhan University, Electronic Information School, Wuhan, China

Yong Ai, Xin Shan

Wuhan University, Electronic Information School, Wuhan, China

Collaborative Innovation Center of Geospatial Technology, Wuhan, China

Opt. Eng. 56(3), 033105 (Mar 22, 2017). doi:10.1117/1.OE.56.3.033105
History: Received December 14, 2016; Accepted March 7, 2017
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Abstract.  Electro-optical (EO) tracking systems, while exhibiting strong nonlinear characteristics, are difficult to accurately model. Nonlinear resistance torque is proposed to describe the system’s nonlinear phenomenon and the genetic algorithm is used to identify model parameters. The model’s root-mean-square error (RMSE) was reduced using nonlinear resistance torque by 2.5 times compared to the Stribeck friction model and by 12 times compared to the linear model. Under the identified model, the system’s nonlinearity was effectively compensated. The results demonstrate the feasibility of the proposed method for the identification of EO tracking systems.

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© 2017 Society of Photo-Optical Instrumentation Engineers

Citation

Yixiang Lin ; Yong Ai and Xin Shan
"Identification of electro-optical tracking systems using genetic algorithms and nonlinear resistance torque", Opt. Eng. 56(3), 033105 (Mar 22, 2017). ; http://dx.doi.org/10.1117/1.OE.56.3.033105


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