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This article presents two different techniques for oscillation control of Quarter-car passive suspension of a vehicle. A mathematical analysis of the proposed system has been done and simulated using an auto-tuned proportional-integral-derivative (PID) controller. The results of PID were further used for training of an artificial neural network (ANN) controller. The primary aim is to stabilise the system in minimal settling time and overshoot range. The ANN controller has been trained using Levenberg–Marquardt algorithm and output was monitored in terms of settling time and maximum percentage overshoot response. The results clearly indicate that ANN model gives superior responses than PID controller.

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PID and Neural Network Control Design for Quarter-Car Passive Suspension System

  • 会议论文

  • 发表日期：

    2025年

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  • Ashwani Kharola,
  • Vishwjeet Choudhary,
  • Rahul,
  • Deepak Juyal,
  • Ajay Kumar,
  • Arvind Kumar,
  • Tarun Kumar Dhiman,
  • Kumar Garv

摘要

This article presents two different techniques for oscillation control of Quarter-car passive suspension of a vehicle. A mathematical analysis of the proposed system has been done and simulated using an auto-tuned proportional-integral-derivative (PID) controller. The results of PID were further used for training of an artificial neural network (ANN) controller. The primary aim is to stabilise the system in minimal settling time and overshoot range. The ANN controller has been trained using Levenberg–Marquardt algorithm and output was monitored in terms of settling time and maximum percentage overshoot response. The results clearly indicate that ANN model gives superior responses than PID controller.