Volume 42 Issue 9
Sep.  2016
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LYU Shuaishuai, LIN Hui. Composite control for electric dynamic loading system based on fractional order iterative learning[J]. Journal of Beijing University of Aeronautics and Astronautics, 2016, 42(9): 1944-1951. doi: 10.13700/j.bh.1001-5965.2015.0543(in Chinese)
Citation: LYU Shuaishuai, LIN Hui. Composite control for electric dynamic loading system based on fractional order iterative learning[J]. Journal of Beijing University of Aeronautics and Astronautics, 2016, 42(9): 1944-1951. doi: 10.13700/j.bh.1001-5965.2015.0543(in Chinese)

Composite control for electric dynamic loading system based on fractional order iterative learning

doi: 10.13700/j.bh.1001-5965.2015.0543
Funds:  National Natural Science Foundation of China (51407143); Specialized Research Fund for the Doctoral Program of Higher Education of China (20136102120049)
  • Received Date: 24 Aug 2015
  • Publish Date: 20 Sep 2016
  • To solve the problem of surplus torque, a composite torque controller is proposed for electric dynamic loading system where the position and torque closed-loops are applied for feedback control and the iterative learning control is applied for feedforward compensation. To improve the dynamic response and reduce the complexity of the system model, direct torque control is used for the permanent magnet synchronous motors. The mathematical model of the electric dynamic loading system is established in frequency domain. The traditional PID and iterative learning control are replaced by fractional order PIλDμ for position and torque closed-loops. Fractional order iterative learning control is used for feedforward compensation. The dynamic response and robustness of the controller are enhanced owing to the information memory characteristics of fractional order calculus. The convergence conditions of the fractional order PD-type iterative learning control are presented through theoretical analysis. Experiments on the loading torque with sinusoidal and trapezoidal wave torque and testing of the surplus torque suppression were performed. The experimental results prove that the controllers are effective in achieving a better torque tracking and restraining the surplus torque for the electric dynamic loading system.

     

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