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In automotive engineering, car suspension systems often employ Proportional Derivative (PD) controllers to enhance performance. PD controllers are utilized to adjust the damping force in response to road conditions. A controller, acting as an amplifier with a constant gain, demonstrates proportional control, with output directly mirroring input.
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Adaptive neuro-fuzzy inference control for active stabilizer bars based on multiple data sources.

Tuan Anh Nguyen1

  • 1Thuyloi University, Hanoi, Vietnam.

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|September 10, 2024
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Summary
This summary is machine-generated.

This study introduces an intelligent control system using adaptive neuro-fuzzy inference system (ANFIS) to enhance vehicle stability. The ANFIS-controlled active stabilizer bars significantly reduce rollover risk and improve wheel-road interaction during steering maneuvers.

Keywords:
ANFISActive stabilizer barintelligent controlrollover phenomenonvehicle dynamics

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Area of Science:

  • Automotive Engineering
  • Control Systems
  • Artificial Intelligence

Background:

  • Vehicle rollover is a critical safety concern during steering maneuvers.
  • Traditional anti-roll systems have limitations in actively managing vehicle dynamics.
  • Intelligent control offers potential for advanced stability enhancement.

Purpose of the Study:

  • To develop and evaluate an adaptive neuro-fuzzy inference system (ANFIS) for controlling active stabilizer bars.
  • To demonstrate the superiority of ANFIS over PID and passive systems in preventing vehicle rollover.
  • To improve vehicle stability and wheel-road interaction during dynamic steering conditions.

Main Methods:

  • Implementation of an ANFIS algorithm to control active anti-roll systems.
  • Training the ANFIS using carefully selected data from previous studies.
  • Comparative simulation analysis against Proportional-Integral-Derivative (PID) and passive (mechanical) systems.

Main Results:

  • ANFIS significantly reduced the roll angle from 8.15° to 6.87°, outperforming PID (7.08°) and passive (7.80°) systems.
  • ANFIS control increased vertical wheel force from 671.06 N to 3030.40 N, enhancing stability.
  • Rollover was prevented at high speeds (80-90 km/h) with ANFIS, unlike systems without active bars.

Conclusions:

  • ANFIS provides a highly effective intelligent control solution for active anti-roll systems.
  • The proposed ANFIS controller ensures robust vehicle rolling stability across various driving conditions.
  • Active stabilizer bars managed by ANFIS offer superior performance in preventing rollover and maintaining tire contact.