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

Yixiang Lin; Yong Ai; Xin Shan

doi:10.1117/1.OE.56.3.033105

22 March 2017 Identification of electro-optical tracking systems using genetic algorithms and nonlinear resistance torque

Yixiang Lin, Yong Ai, Xin Shan

Author Affiliations +

Optical Engineering, Vol. 56, Issue 3, 033105 (March 2017). https://doi.org/10.1117/1.OE.56.3.033105

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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Yixiang Lin, Yong Ai, and Xin Shan "Identification of electro-optical tracking systems using genetic algorithms and nonlinear resistance torque," Optical Engineering 56(3), 033105 (22 March 2017). https://doi.org/10.1117/1.OE.56.3.033105

Received: 14 December 2016; Accepted: 7 March 2017; Published: 22 March 2017

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