Volume 41 Issue 3
May  2021
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ZHOU Guoguang, JIN Guang, XU Wei, PIAO Yongjie, CHANG Lin. Automatic Balancing Control of Air-bearing Simulator Based on Firefly Algorithm Improved Neural Network[J]. Journal of Space Science, 2021, 41(3): 483-490. doi: 10.11728/cjss2021.03.483
Citation: ZHOU Guoguang, JIN Guang, XU Wei, PIAO Yongjie, CHANG Lin. Automatic Balancing Control of Air-bearing Simulator Based on Firefly Algorithm Improved Neural Network[J]. Journal of Space Science, 2021, 41(3): 483-490. doi: 10.11728/cjss2021.03.483

Automatic Balancing Control of Air-bearing Simulator Based on Firefly Algorithm Improved Neural Network

doi: 10.11728/cjss2021.03.483
  • Received Date: 2019-10-30
  • Rev Recd Date: 2020-03-11
  • Publish Date: 2021-05-15
  • In order to accurately reproduce the multi-satellite networking technology and simulate the multi-mode high-resolution imaging process on the ground, the three-axis air-bearing test bed was the key device of simulation. In this paper, a fast automatic balance adjustment control algorithm was proposed based on firefly algorithm improved BP (Back Propagation) neural network PID (Proportion Integration Differentiation) control. Aiming at the problem of long adjustment time and easy to obtain a non-optimal solution, the firefly algorithm was introduced to optimize the initial weight and threshold value of the BP neural network, and improve the algorithm performance in convergence rate and stability. Based on the kinematics and dynamics model of the three-axis air-bearing simulator platform, the simulation results show that the optimized algorithm reduces the x-axis centroid offset to 2.3×10-7m in 3.1s. The algorithm has faster and higher stability on air-bearing simulator automatic balancing control, and satisfies the demand for multi-satellite imaging process simulation.

     

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