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ACTA AERONAUTICAET ASTRONAUTICA SINICA ›› 2021, Vol. 42 ›› Issue (6): 624540-624540.doi: 10.7527/S1000-6893.2020.24540

• Special Topic of Avionics and Utility Systems • Previous Articles     Next Articles

Fast terminal sliding mode control of neural networks for aeromechanical actuators

WEI Kepeng, HU Jian, YAO Jianyong, XING Haochen, LE Guigao   

  1. School of Mechanical Engineering, Nanjing University of Science and Technology, Nanjing 210094, China
  • Received:2020-07-16 Revised:2020-08-03 Online:2021-06-15 Published:1900-01-01
  • Supported by:
    National Natural Science Foundation of China(51975294); Open subject fund project of State Key Laboratory of High Performance Complex Manufacturing(Kfkt2019-11)

Abstract: Electromechanical actuators are increasingly favored by the aviation industry because of their advantages such as cleanness and easy maintenance, and the aviation electromechanical actuators have characteristics of high control accuracy, high stability and fast response speed. To further improve the response speed and tracking accuracy of aviation actuators, this paper proposes a fast terminal sliding mode control strategy based on multi-layer neural network, which can speed up the system response and realize the system limited time stability without disturbances. Aiming at the uncertainty of system parameters and external disturbances, we design a multi-layer neural network for estimation and compensation by the feedforward method. A nonlinear robust term is designed to overcome the reconstruction error of the neural network. The Lyapunov stability theorem proves that the control system can achieve bounded stability under disturbances. The experimental results show good parameter adaptation and anti-jamming capabilities, higher tracking accuracy and faster response speed of the designed controller.

Key words: aeromechanical actuators, fast terminal sliding mode control, neural network control, nonlinear control, model uncertainty

CLC Number: