基于模糊PID的路径跟踪控制系统
Path Tracking Control System Based on Fuzzy PID
DOI: 10.12677/CSA.2020.103055, PDF,    科研立项经费支持
作者: 王金星*：山东农业大学机械与电子工程学院，山东 泰安;山东省农业装备智能化工程实验室，山东 泰安；石绍军, 李玉风, 宋悦, 权泽堃：山东农业大学机械与电子工程学院，山东 泰安；刘双喜, 王玉亮：山东农业大学机械与电子工程学院，山东 泰安;山东省园艺机械与装备重点实验室，山东 泰安
关键词: 插秧机；自动导航；路径跟踪；模糊PID；Transplanter； Automatic Navigation； Path Tracking； Fuzzy PID
摘要: 为提高自动导航插秧机路径跟踪控制系统性能，提出一种基于模糊PID算法调整插秧机前轮转向角度的控制方法。该方法首先建立被控对象的运动学模型，根据运动学模型对模糊PID控制算法进行设计。其次运用Matlab对路径跟踪控制系统进行仿真分析，仿真结果表明：所设计模糊PID控制方法相比于传统PID控制方法，可以有效减少系统的超调量和到达稳态的时间。最后进行动态试验验证，传统PID控制方法下，小车底盘以0.35和0.85 m/s的速度行驶时，最大路径跟踪误差为3.8和6.5 cm，平均路径跟踪误差为2.47和3.67 cm；在模糊PID控制方法下，小车底盘以0.35和0.85 m/s的速度行驶时，最大路径跟踪误差为2.1和4.8 cm，平均路径跟踪误差为1.57和2.7 cm；试验表明：模糊PID控制性能优于传统PID算法，更适合于插秧机路径跟踪控制。
Abstract: In order to improve the performance of the path tracking control system of the automatic naviga-tion transplanter, a control method based on the fuzzy PID algorithm to adjust the steering angle of the front wheel of the transplanter is proposed. Firstly, the kinematic model of the controlled object is established, and the fuzzy PID control algorithm is designed according to the kinematic model. Secondly, Matlab is used to simulate the path tracking control system. The results show that the performance of the fuzzy PID control method is better than the traditional PID control method, which can effectively reduce the overshoot of the system and the time to reach the steady state. Finally, the dynamic test is carried out to verify that under the traditional PID control method, the maximum path tracking error is 3.8 and 6.5 cm, and the average path tracking error is 2.47 and 3.67 cm when the car chassis is running at the speed of 0.35 and 0.85 m/s; under the fuzzy PID control method, the maximum path tracking error is 2.1 and 4.8cm, and the average path tracking error is 1.57 and 2.7 cm when the car chassis is running at the speed of 0.35 and 0.85m/s. The experiment shows that the performance of fuzzy PID control is better than that of traditional PID algorithm, and it is more suitable for path tracking control of transplanter.
文章引用：王金星, 石绍军, 刘双喜, 王玉亮, 李玉风, 宋悦, 权泽堃. 基于模糊PID的路径跟踪控制系统[J]. 计算机科学与应用, 2020, 10(3): 529-540. https://doi.org/10.12677/CSA.2020.103055

参考文献

[1] 谭晨佼, 李轶林, 王东飞, 毛文菊, 杨福增. 农业机械自动导航技术研究进展[J]. 农机化研究, 2020, 42(5): 7-14+32.
[2] 迟德霞, 任文涛, 由佳翰, 王洋, 李萍. 水稻插秧机导航控制器设计与路径追踪仿真研究[J]. 沈阳农业大学学报, 2016, 47(3): 363-367.
[3] Wallace, R., Stentz, A., Thorpe, C.E., et al. (1985) First Results in Robot Road-Following. Proceedings of 9th IJCAI, Los Angeles, 18-23 August 1985, 1089-1095.
[4] Amidi, O. and Thorpe, C.E. (1991) Integrated Mobile Robot Control. In: Fibers 91, International Society for Optics and Photonics, Boston, 504-523. [Google Scholar] [CrossRef] 
[5] 黄沛琛, 罗锡文, 张智刚. 改进纯追踪模型的农业机械地头转向控制方法[J]. 计算机工程与应用, 2010, 46(21): 216-219.
[6] 王辉, 王桂民, 罗锡文, 张智刚, 高阳, 何杰, 岳斌斌. 基于预瞄追踪模型的农机导航路径跟踪控制方法[J]. 农业工程学报, 2019, 35(4): 11-19.
[7] 刘正铎, 张万枝, 吕钊钦, 郑文秀, 穆桂脂, 程向勋. 扰动下农用运输车辆路径跟踪控制器设计与试验[J]. 农业机械学报, 2018, 49(12): 378-386.
[8] 邹凯. 基于增量线性模型预测控制的无人车轨迹跟踪方法[C]//中国汽车工程学会. 2019中国汽车工程学会年会论文集(1), 北京: 中国汽车工程学会, 2019: 115.
[9] 周建军, 张漫, 汪懋华, 等. 基于模糊控制的农用车辆路线跟踪[J]. 农业机械学报, 2009, 40(4): 151-156.
[10] Richa Sharma, K.K., Deepak, P.G. and Deepak, J. (2020) An Optimal Interval Type-2 Fuzzy Logic Control Based Closed-Loop Drug Ad-ministration to Regulate the Mean Arterial Blood Pressure. Computer Methods and Programs in Biomedicine, 185, Article ID: 105167. [Google Scholar] [CrossRef] [PubMed]
[11] 罗锡文, 张智刚, 赵祚喜, 陈斌, 胡炼, 吴晓鹏. 东方红X-804拖拉机的DGPS自动导航控制系统[J]. 农业工程学报, 2009, 25(11): 139-145.
[12] Bogler, A., Kastl, A., Spinnler, M., Sattelmayer, T., Beer, A. and Bar-Zeev, E. (2020) Particle Counting and Tracking: Zooming on Deposition and Flow Paths during Initial Stages of Cake Formation in Forward Osmosis with Spacers. Journal of Membrane Science, 597, Article ID: 117619. [Google Scholar] [CrossRef] 
[13] 张曾科. 模糊数学在自动化技术中的应用[M]. 北京: 清华大学出版社, 1997.
[14] 童后权. 直流无刷电机中数字式PID控制算法的应用分析[J]. 数字技术与应用, 2014(9): 123.
[15] Bouakkaz, M.S., Boukadoum, A., Boudebbouz, O., Fergani, N., Boutasseta, N., Attoui, I., Bouraiou, A. and Necaibia, A. (2020) Dynamic Performance Evaluation and Improvement of PV Energy Generation Systems Using Moth Flame Optimization with Combined Fractional Order PID and Sliding Mode Controller. Solar Energy, 199, 411-424. [Google Scholar] [CrossRef]