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陆钰,李丹,赵文杰. 基于前馈型变论域模糊PID控制的智能小车轨迹跟踪方法[J]. 安徽工业大学学报(自然科学版),2024,41(3):1-8. doi: 10.12415/j.issn.1671-7872.23150
引用本文: 陆钰,李丹,赵文杰. 基于前馈型变论域模糊PID控制的智能小车轨迹跟踪方法[J]. 安徽工业大学学报(自然科学版),2024,41(3):1-8. doi: 10.12415/j.issn.1671-7872.23150
LU Yu, LI Dan, ZHAO Wenjie. Intelligent Trolley Trajectory Tracking Method Based on Feed-forward Type Variable Theory Domain Fuzzy PID Control[J]. Journal of Anhui University of Technology(Natural Science). DOI: 10.12415/j.issn.1671-7872.23150
Citation: LU Yu, LI Dan, ZHAO Wenjie. Intelligent Trolley Trajectory Tracking Method Based on Feed-forward Type Variable Theory Domain Fuzzy PID Control[J]. Journal of Anhui University of Technology(Natural Science). DOI: 10.12415/j.issn.1671-7872.23150

基于前馈型变论域模糊PID控制的智能小车轨迹跟踪方法

Intelligent Trolley Trajectory Tracking Method Based on Feed-forward Type Variable Theory Domain Fuzzy PID Control

  • 摘要: 为提高智能小车轨迹跟踪的精度及抗干扰能力,提出1种基于前馈型变论域模糊控制方法。以自动导向小车(automated guided vehicle,AGV)为研究对象,建立小车运动学模型对其进行动力学分析;在保持主控制参数不变的情况下,将前馈控制加入变论域模糊控制,搭建前馈型变论域模糊PID(proportional-integral-derivative)控制系统,通过变论域模糊PID控制调整参数使系统获得较好的稳定性,再通过调整前馈控制参数使系统的目标跟踪性能达到最佳;设定S形曲线跟踪路线,在Matlab/Simulink平台下搭建传统PID、模糊PID、变论域模糊PID及前馈型变论域模糊PID等4种控制模型进行仿真实验,比较验证本文方法的控制性能。结果表明:无干扰情况下,4种控制方法的车辆转弯最大横向偏差分别为0.258 0,0.198 8,0.179 2和0.112 5 m,本文方法的偏差最小,轨迹跟踪精度最高;模拟真实路况下,4种控制方法的车辆转弯最大横向偏差分别为0.891 7,0.820 9,0.791 7,0.683 3 m,本文方法的偏差依然最小,抗干扰能力最强,验证了本文所提控制方法兼具跟踪高精度和良好稳定性的优点。

     

    Abstract: In order to improve the accuracy and anti-interference ability of intelligent trolley of intelligent vehicle trajectory tracking, a fuzzy control method based on feed-forward type variable theory domain was proposed. Taking the automated guided vehicle (AGV) as the research object, the kinematic model of the vehicle was established to analyze the dynamics of the vehicle. Under the condition of keeping the main control parameters unchanged, the feedforward control was added into the variable-theoretic domain fuzzy control to build the feedforward variable-theoretic domain fuzzy PID control system, and then the parameters were adjusted through the variable-theoretic domain fuzzy PID control to obtain a better stability, and then the target tracking performance of the system was optimized through the adjustment of the feedforward control parameters. The system was adjusted by the variable domain fuzzy PID control parameters to obtain better stability, and then the feedforward control parameters were adjusted to make the system’s target tracking performance reach the best. An S-shaped curve tracking route was set up and the simulation experiments on four control models, including traditional PID, fuzzy PID, variable universe fuzzy PID, and feedforward variable universe fuzzy PID were conducted on the Matlab/Simulink platform to compare and verify the control performance of the proposed method.The results show that under the condition of no interference, the maximum lateral deviation of vehicle turning of the four control methods are 0.258 0, 0.198 8, 0.179 2 and 0.112 5 m, respectively, and the method of this paper has the smallest deviation and the highest trajectory tracking accuracy. Under the simulation of the real road conditions, the maximum lateral deviation of vehicle turning of the four control methods are 0.891 7, 0.820 9, 0.791 7, 0.683 3 m, and the deviation of this paper’s method is still the smallest, and the anti-interference ability is the strongest, which confirms that the control method proposed in this paper possesses the dual advantages of high tracking precision and excellent stability.

     

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