Transactions on Machine Intelligence

Transactions on Machine Intelligence

Control of Vehicle Active Suspension System Using Neural Network

Document Type : Original Article

Authors
1 Masters Student, Control Engineering, Iran University of Science and Technology, Tehran, Iran.
2 Masters Student, Control Engineering, Iran University of Science and Technology, Tehran, Iran
Abstract
The primary cause of vehicle vibration stems from road irregularities. Addressing this, an effective strategy involves implementing a robust artificial neural network control system to manage the vehicle suspension system's vibrations. To achieve comprehensive vibration control for the entire suspension system, a robust neural network-based control system is employed. The complete vehicle system operates with 7 degrees of freedom, encompassing vertical axis motion, angular variations around the X axis, and angular changes around the Y axis of the car chassis. The proposed control system integrates a robust controller, a neural controller, and a neural network model tailored for the vehicle suspension system. To assess simulation outcomes, a proportional integral derivative (PID) controller is utilized for overall vehicle suspension system vibration control. The study introduces random road roughness as a disturbance factor applied to the proposed control system. Simulation results affirm that the suggested neural control system demonstrates highly effective control performance, with minimal error in adapting to unexpected road disturbances affecting the vehicle suspension.
Keywords

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Volume 7, Issue 2
Winter 2024
Pages 107-135

  • Receive Date 07 March 2024
  • Revise Date 13 April 2024
  • Accept Date 05 June 2024