Control Strategy for Space Manipulator Based on Genetic Algorithm Self-Tuning

Chao Wang; Zheng Hong Dong; Yong Ming Gao; Hang Yin

doi:10.4028/www.scientific.net/AMR.706-708.695

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HomeAdvanced Materials ResearchAdvanced Materials Research Vols. 706-708Control Strategy for Space Manipulator Based on...

Control Strategy for Space Manipulator Based on Genetic Algorithm Self-Tuning

Abstract:

For questions of joint angle control of space manipulator, a method based on genetic algorithm PID self-tuning is proposed, which can improve the control accuracy of joint angle. We establish the dynamic model of the space manipulator and design the PID controller, and then using the genetic algorithm to tuning the PID parameters, and simulate in MATLAB. The result shows that the control performance of the space manipulator is improved, and the difficulties of traditional PID parameter regulation can be avoided by this method.

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Periodical:

Advanced Materials Research (Volumes 706-708)

Pages:

695-699

DOI:

https://doi.org/10.4028/www.scientific.net/AMR.706-708.695

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Online since:

June 2013

Authors:

Chao Wang, Zheng Hong Dong, Yong Ming Gao, Hang Yin

Keywords:

Genetic Algorithm (GA), PID Control, Self-Tuning Method, Space Manipulator

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References

[1] Menon C, Busolo S, Cocuzza S, et al. Issues and new solutions for testing free-flying robots [J]. IAC-04-IAF-1.2004, (5): 1-11.

Google Scholar

[2] Kasai T, Oda M, Suzuki T. Results of the ETS-7 Mission rendezvous Docking and Space Robotics Experiments [C]. 5th International Symposium on Artificial Intelligence, Robotics and Automation in Space, The Netherlands, 1999, pp.299-306.

Google Scholar

[3] Liang B, Li C, Xue L and Qiang W. A Chinese Small Intelligent Space Robotic System for on-Orbit Servicing [C]. International Conference on Intelligent Robots and Systems, Inst. Of Electrical and Electronics Engineers, New York, Oct. 2006, pp.4602-4607.

DOI: 10.1109/iros.2006.282166

Google Scholar

[4] Bergmann E, Waller B, Levy D. Mass Property Estimation for Control of Asymmetrical Satellites [J]. Journal of Guidance, Control and Dynamics, Vol.10, No. 5, 987, pp.483-491.

DOI: 10.2514/3.20243

Google Scholar

[5] Kelkar A G, Joshi S M, Albersts T E, et al. Dissipative controllers for nonlinear mufti-body flexible space systems[J].Journal of Guidance, Control, and Dynamics, 1995, 18(5): 1044-1052.

DOI: 10.2514/3.21503

Google Scholar

[6] T R Kane, P W Lilcins, D A Levinson. Spacecraft Dynamics[M], McGraw-Hill, NewYork, 1983:1-7.

Google Scholar

[7] YALCINOZ T, AITUN H. Power Economic Dispatch Using a Hybrid Genetic Algorithm[J]. IEEE Power Engineering Review, 2001, 2:59-60.

DOI: 10.1109/39.911360

Google Scholar

[8] Xu Wenfu. Path Planning and Experiment Study of Space Robot for Target Capturing[D].Harbin Institute of Technology, 2007.

Google Scholar