Adaptive Control Scheme for Dual Drive Electro Servo-Hydraulic System Based on Self-Recurrent Wavelet Neural Network

Document Type : Original Article

Authors

1 Control Group, Faculty of Electrical Engineering, Malk-Ashtar University of Technology

2 Control Group. Faculty of Electrical Engineering,

Abstract

The motion control systems based on hydro motors, due to the nonlinear and time variant behavior, are complex systems for accurate control. IN this paper, an adaptive control scheme based on self-recurrent wavelet neural network is presented to control dual drive electro servo-hydraulic system. The proposed control scheme does not require the exact dynamical model of the system. As a result, this method will be appropriate for severe nonlinear systems such as electro servo-hydraulic system. In addition to identifying the dynamic of the system, the proposed neural network is trained to predict one-step ahead of the system output. The training process is implemented by employing a novel optimization algorithm called flexible particle swarm optimization (FPSO) algorithm. In order to enhance the performance of this system, two electro servo-hydraulic systems are connected to each other to increase the bandwidth. The controller provided for the electro-servo-hydraulic system is simulated regarding to the unknown dynamic of the system, and the simulation results confirm the effectiveness of the proposed control scheme.

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History

  • Receive Date: 14 March 2020
  • Accept Date: 07 April 2020
  • First Publish Date: 22 July 2020

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