The Satellite Attitude Control Law Design Based on Machine Learning

Abstract:

Traditional optimization algorithms can only optimize parameters in control laws. Machine learning method can optimize parameters and evolve satellite attitude control law automatically under certain criterion. Single axis satellite attitude simulation system with noise was built up, which included satellite attitude dynamic model, sensors and actuators model. The control laws inputs were attitude error, attitude errors integral and angular velocity error, and outputs were actuators control instructions. Control laws fitness function was an attitude errors statistical function. With suitable function set selected for genetic programming (GP) and parse tree used to represent a control law expression, GP was used to evolve control law expression automatically. Simulation result shows that this method can evolve control law with uncertainties noise better. The evolved control law response and control precision are better than PID, and it can be used in satellite attitude control.

• Periodical: Applied Mechanics and Materials (Volumes 519-520)
• Pages: 741-746
• DOI: https://doi.org/10.4028/www.scientific.net/AMM.519-520.741
• Online since: February 2014
• Authors: Guo Jiang Sun, Jin Hui Li*, Shi Ming Chen, Yun Feng Dong
• Keywords: Attitude, Control, Genetic Programming, Machine Learning, Satellite

References

[1] Liu Housheng. The study on knowledge discovery based on uncertainty theory and machine learning [D]. Hei Fei: University of Science and Technology of China, 2008. (In Chinese).

[2] Koza J R. Genetic Programming: On the Programming of computers by means of Natural Selection. Cambridge, MA: MIT Press, (1992).

[3] Koza J R. Human-competitive results produced by genetic programming. Genetic Programming and Evolvable Machines, 3rd ed., vol. 11, 2010, pp.251-284.

DOI: 10.1007/s10710-010-9112-3

[4] Jiang Yiheng. Modeling and Synthesizing the Coordinate Control System Based on Genetic Programming [D]. Bei Jing: North China Electric Power University, 2008. (In Chinese).

[5] Liu Jun and Han Chao. Nonlinear Control of Attitude Maneuver for Satellite Using Varible Speed Control Movement Gyros [J]. Aerospace Control, 5th ed., vol. 25, 2007, pp.33-38. (In Chinese).

[6] Yoon H and Tsiotras P. Adaptive spacecraft attitude tracking control with actuator uncertainties. AIAA Guidance, Navigation, and Control Conference, AIAA-2005-6392.

DOI: 10.2514/6.2005-6392

[7] Wang Lei and Zhao Yushan. Sliding Mode Attitude Control Using Momentum Exchange Device [J]. Journal of Beijing University of Aeronautics and Astronautics, 11th ed., vol. 35, 2009, pp.1388-1392. (In Chinese).

[8] Zhao Chunsheng, Li Zhirong and Zhao Xiangdong. The Review on Modeling Methods of the Ultrasonic Motor Electrome chanical Coupling System [J]. Micromotors, 4th ed., vol. 36, 2003, pp.41-44. (In Chinese).

[9] Das H, Bao X, Bar-cohen Y, et al. Robot manipulator technologies for planetary exploration. Proceeding of the 6th Annual International Symposium on Smart Structures and Materials, California, USA, (1999).

[10] Dong Yunfeng, Chen Shiming, Zhang Zhenjun, et al. An Attitude Control Apparatus Drove by Ultrasonic Motor [P]: China, ZL200810074709. 0 [P]. 2010-02-17. (in Chinese).