{"title":"Realization of Fuzzy-PI Controller-Based Path Planning of Differential Drive Mobile Robot","authors":"Ahmet Top, Muammer Gökbulut","doi":"10.55525/tjst.1423794","DOIUrl":null,"url":null,"abstract":"This paper uses a cascade-connected fuzzy-PI controller to control the position and speed of a differential drive and four-wheel drive of an autonomous mobile robot for optimal path planning. The angular speed information obtained from the encoder of each motor and the instantaneous position and angle information of the robot were calculated. The angle and position error between the reference points and these values is applied to the fuzzy logic controller as an input signal. The robot angular and linear speed data obtained from the fuzzy logic output were converted into reference speed values with kinematic equations to be applied to the motors. The speed controls of the motors were carried out with a PI controller based on these reference values. The study was performed both as a simulation in the MATLAB program and experimentally in the laboratory environment for one and more reference coordinates. In the experimental study, reference values were sent to the robot via Bluetooth with the Android application designed. At the same time, the instant data of the robot was also collected on the Android device through the same application. These data collected in Excel format were transferred to the computer via e-mail and the graphics were drawn in the MATLAB program. When the results were examined, it was seen that both speed and position control were successfully implemented with the fuzzy-PI controller for optimum path planning of the robot.","PeriodicalId":516893,"journal":{"name":"Turkish Journal of Science and Technology","volume":"121 13","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2024-03-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Turkish Journal of Science and Technology","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.55525/tjst.1423794","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
This paper uses a cascade-connected fuzzy-PI controller to control the position and speed of a differential drive and four-wheel drive of an autonomous mobile robot for optimal path planning. The angular speed information obtained from the encoder of each motor and the instantaneous position and angle information of the robot were calculated. The angle and position error between the reference points and these values is applied to the fuzzy logic controller as an input signal. The robot angular and linear speed data obtained from the fuzzy logic output were converted into reference speed values with kinematic equations to be applied to the motors. The speed controls of the motors were carried out with a PI controller based on these reference values. The study was performed both as a simulation in the MATLAB program and experimentally in the laboratory environment for one and more reference coordinates. In the experimental study, reference values were sent to the robot via Bluetooth with the Android application designed. At the same time, the instant data of the robot was also collected on the Android device through the same application. These data collected in Excel format were transferred to the computer via e-mail and the graphics were drawn in the MATLAB program. When the results were examined, it was seen that both speed and position control were successfully implemented with the fuzzy-PI controller for optimum path planning of the robot.
本文使用级联模糊 PI 控制器控制自主移动机器人的差动驱动和四轮驱动的位置和速度,以实现最佳路径规划。计算了从每个电机的编码器获得的角速度信息以及机器人的瞬时位置和角度信息。参考点与这些值之间的角度和位置误差作为输入信号应用于模糊逻辑控制器。从模糊逻辑输出中获得的机器人角度和线速度数据被转换成带有运动学方程的参考速度值,并应用于电机。根据这些参考值,使用 PI 控制器对电机进行速度控制。这项研究既在 MATLAB 程序中进行了模拟,也在实验室环境中对一个和多个参考坐标进行了实验。在实验研究中,参考值通过设计的安卓应用软件通过蓝牙发送到机器人。与此同时,机器人的即时数据也通过同一应用程序收集到安卓设备上。这些以 Excel 格式收集的数据通过电子邮件传送到计算机,并在 MATLAB 程序中绘制图形。检查结果表明,使用模糊 PI 控制器成功地实现了速度和位置控制,从而实现了机器人的最佳路径规划。