Traffic & Transportation Engineering

Active Disturbance Rejection Control of Active Stabilizer System Based on Particle Swarm Optimization

  • ZHAO Qiang ,
  • LIU Chuanwei ,
  • ZHANG Na ,
  • ZHU Baoquan ,
  • XIE Chunli
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  • 1.College of Mechanical and Electrical Engineering,Northeast Forestry University,Harbin 150040,Heilongjiang,China
    2.School of Electrical and Control Engineering,Heilongjiang University of Science and Technology,Harbin 150022,Heilongjiang,China
赵强(1971-),男,教授,博士生导师,主要从事车辆动力学及控制研究。E-mail:zhaoqiang@nefu.edu.cn

Received date: 2022-08-19

  Online published: 2022-12-05

Supported by

the Key Projects of National Key Research & Development Program of China(2017YFC0803901);the Heilongjiang Province Key Research & Development Project(JD22A014);the Natural Science Foundation of Heilongjiang Province(LH2021F002)

Abstract

In order to improve the anti-roll ability of vehicle, this paper designed a hydraulic motor-driven active stabilizer control system, and proposed a hierarchical control strategy based on particle swarm optimization (PSO) algorithm. The upper active disturbance rejection controller (ADRC) calculates the anti-roll torque required by the whole vehicle, and the anti-roll torque required by the whole vehicle is distributed to the front and rear axles through a distributor. The lower three-loop proportional-integral-differential (PID) controller receives the anti-roll torque to be provided, calculates the control current and inputs it to the servo valve, so as to drive the motor output shaft to rotate and generates the active torque through the stabilizer bar to realize the active anti-roll control of the vehicle. In order to make the controller has better control effect, the PSO algorithm was used to optimize the upper and lower control as a whole, and the optimized ADRC and PID parameters were input into the vehicle model. In order to make the simulation close to the actual effect, the torsional stiffness of the lateral stabilizer bar measured by the experiment was also brought into the model. The serpentine and double lane shifting conditions were used for simulation on Class C road surface, and the simulation verification was carried out by comparing PSO-optimized ADRC system with passive system, PID control system and unoptimized ADRC system. The simulation data show that the roll angle directly affects the vehicle’s roll stability, the hierarchical control strategy optimized by PSO algorithm can significantly reduce the vehicle’s roll angle, and effectively suppress the instability caused by excessive body roll motion. The active control stabilizer can better provide the required anti-roll torque for the vehicle than the traditional passive stabilizer, and improve the anti-roll ability of the vehicle. The optimized ADRC controller has better active control effect than the passive system and the unoptimized ADRC controller. Under the same working condition, the roll angle is smaller, the anti-roll ability is stronger, the optimized three closed-loop PID response speed is faster, and the tracking performance is better.

Cite this article

ZHAO Qiang , LIU Chuanwei , ZHANG Na , ZHU Baoquan , XIE Chunli . Active Disturbance Rejection Control of Active Stabilizer System Based on Particle Swarm Optimization[J]. Journal of South China University of Technology(Natural Science), 2023 , 51(6) : 52 -61 . DOI: 10.12141/j.issn.1000-565X.220535

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