基于最优偏差路径的自动导引车纠偏方法
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摘要
针对使用二维码作为定位模块的视觉自动导引车(AGV)的轨迹跟踪问题,提出了一种基于最优偏差路径的模糊PID纠偏算法。首先建立AGV的运动学方程,将横向偏差和航向偏差作为控制系统的输入变量;其次引入Hamilton最优控制函数,得到基于最优偏差转化策略的AGV最优偏差路径和最优控制方程;最后以AGV与最优偏差路径之间的位姿偏差更新模糊PID控制器的参数,实时调节驱动轮的差速,使AGV按最优偏差路径行驶,实现AGV纠偏的最优控制。实验结果表明,该方法可以平稳、快速地消除横向和航向偏差,本文控制方法在极端偏差状态下的4种隶属度区间的横向偏差纠偏结果分别为2.38、2.54、3.29和4.43 mm,均不超过5 mm,纠偏距离小于1.2 m,跟踪精度为3.2 mm,既提高无轨导引AGV的导航精度,也能较好地满足系统运行的稳定性和伺服驱动能力。
Aiming at trajectory tracking of the vision-guided AGV with two-dimension code,a fuzzy PID rectification algorithm based on optimal deviation path is proposed. Firstly,the kinematics equation of the AGV is established,using the lateral deviation and course deviation as the input variables of the control system. Secondly,the optimal deviation path and optimal control equation are obtained based on the optimal deviation transformation strategy by introducing the Hamilton optimal control function. Finally,the fuzzy PID controller's parameters are updated according to pose error between the AGV and the optimal deviation path,to achieve the differential velocity adjusting real time. As a result,the AGV drives along the optimal deviation path, and achieves optimal control. The experimental results show that the proposed method can eliminate the lateral and course deviation smoothly and quickly. In extreme deviation,the four kinds of membership interval deviation correction results of this method are 2. 38,2. 54,3. 29 and 4. 43 mm. The results are all less than 5 mm,and the rectification distance is less than 1.2 m,and trajectory tracking accuracy is 3.2 mm.Not only the navigation precision improves,but also the stability of the operation and driving capability of the non-track AGV are met.
Aiming at trajectory tracking of the vision-guided AGV with two-dimension code,a fuzzy PID rectification algorithm based on optimal deviation path is proposed. Firstly,the kinematics equation of the AGV is established,using the lateral deviation and course deviation as the input variables of the control system. Secondly,the optimal deviation path and optimal control equation are obtained based on the optimal deviation transformation strategy by introducing the Hamilton optimal control function. Finally,the fuzzy PID controller's parameters are updated according to pose error between the AGV and the optimal deviation path,to achieve the differential velocity adjusting real time. As a result,the AGV drives along the optimal deviation path, and achieves optimal control. The experimental results show that the proposed method can eliminate the lateral and course deviation smoothly and quickly. In extreme deviation,the four kinds of membership interval deviation correction results of this method are 2. 38,2. 54,3. 29 and 4. 43 mm. The results are all less than 5 mm,and the rectification distance is less than 1.2 m,and trajectory tracking accuracy is 3.2 mm.Not only the navigation precision improves,but also the stability of the operation and driving capability of the non-track AGV are met.
引文
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[22]周向阳,贾媛.航空遥感惯性稳定平台模糊/PID复合控制[J].仪器仪表学报,2016,37(11):2545-2554.ZHOU X Y,JIA Y.Fuzzy/PID compound control for inertially stabilized platform in airborne remote sensing[J].Chinese Journal of Scientific Instrument,2016,37(11):2545-2554.
[2]吴斌,钱晓明,武星,等.自动导引车骨架结构优化设计[J].中国机械工程,2014,25(19):2653-2657,2664.WU B,QIAN X M,WU X,et al.Optimization design on AGV frame structure[J].China Mechanical Engineering,2014,25(19):2653-2657,2664.
[3]石陈陈,楼佩煌,武星,等.自动导引车多摄像机主动导引系统的协同标定[J].仪器仪表学报,2014,35(11):2589-2599.SHI CH CH,LOU P H,WU X,et al.Collaborative calibration of initiative multi-camera guiding system for transport automatic guided vehicle[J].Chinese Journal of Scientific Instrument,2014,35(11):2589-2599.
[4]KIM J,CHO H,KIM S.Positioning and driving control of fork-type automatic guided vehicle with laser navigation[J].International Journal of Fuzzy Logic&Intelligent Systems,2013,13(4):307-314.
[5]贺晶晶,姜平,冯晓荣.基于UWB的无人运输车的导航定位算法研究[J].电子测量与仪器学报,2016,30(11):1743-1749.HE J J,JIANG P,FENG X R.Research on navigation and positioning algorithm for unmanned vehicle based on UWB[J].Journal of Electronic Measurement and Instrumentation,2016,30(11):1743-1749.
[6]罗哉,刘慧平,胡晓峰,等.视觉导引AGV纠偏算法研究[J].计算机仿真,2016,33(1):373-377.LUO Z,LIU H P,HU X F,et al.Research of visionguided AGV deviation-rectifying algorithm[J].Computer Simulation,2016,33(1):373-377.
[7]吴军,于之靖,诸葛晶晶,等.采用红外扫描激光与超声技术的室内空间定位[J].光学精密工程,2016,24(10):2417-2423.WU J,YU ZH Q,ZHUGE J J,et al.Indoor positioning by using scanning infrared laser and ultrasonic technology[J].Optics and Precision Engineering,2016,24(10):2417-2423.
[8]张建鹏,楼佩煌,钱晓明,等.多窗口实时测距的视觉导引AGV精确定位技术研究[J].仪器仪表学报,2016,37(6):1356-1362.ZHANG J P,LOU P H,QIAN X M,et al.Research on precise positioning technology by multi-window and realtime measurement for visual navigation AGV[J].Chinese Journal of Scientific Instrument,2016,37(6):1356-1362.
[9]王红娟,王志鹏,张颖颖,等.利用QR码在光学干涉多图像加密系统中实现信息高质量恢复[J].光学学报,2014,34(9):78-84.WANG H J,WANG ZH P,ZHANG Y Y,et al.Using QR codes in multi-image optical interference encryption system to reconstruct high quality original information[J].Acta Optica Sinica,2014,34(9):78-84.
[10]熊用,汪鲁才,艾琼龙.基于相关匹配的QR码识别方法[J].仪器仪表学报,2011,32(3):571-576.XIONG Y,WANG L C,AI Q L.QR code recognition method based on correlation match[J].Chinese Journal of Scientific Instrument,2011,32(3):571-576.
[11]林威,翟信德,朱长青,等.基于QR码的遥感影像数字水印算法[J].北京邮电大学学报,2015,38(1):26-30.LIN W,ZHAI X D,ZHU CH Q,et al.QR code based research on digital watermark algorithm for remote sensing image[J].Journal of Beijing University of Posts&Telecommunications,2015,34(7):2306-2309.
[12]尹晓红,赵韩,吴焱明,等.基于卡尔曼滤波的自动引导车串级轨迹跟踪控制[J].农业机械学报,2010,41(2):180-184.YIN X H,ZHAO H,WU Y M,et al.Cascade tracking control for AGV based on Kalman filter[J].Transactions of the Chinese Society for Agricultural Machinery,2010,41(2):180-184.
[13]张经天,庄植均,李忠明,等.视觉导引AGV分段预测控制模型设计[J].北京邮电大学学报,2014(4):15-19.ZHANG J T,ZHUANG ZH J,LI ZH M,et al.Model design for the sectionalize predictive control based on vision-guided AGV[J].Journal of Beijing University of Posts and Telecommunications,2014,37(4):15-19.
[14]郭景华,胡平,李琳辉,等.基于遗传优化的无人车横向模糊控制[J].机械工程学报,2012,48(6):76-82.GUO J H,HU P,LI L H,et al.Study on lateral fuzzy control of unmanned vehicles via genetic algorithms[J].Journal of Mechanical Engineering,2012,48(6):76-82.
[15]AMIT A,ILAN Z.Controllers for trajectory tracking and string-like formation in Wheeled Mobile Robots with bounded inputs[C].IEEE Mediterranean Electrotechnical Conference,2010:1563-1568.
[16]PRATAMA P S,GULAKARI A V,SETIAWAN Y D,et al.Trajectory tracking and fault detection algorithm for automatic guided vehicle based on multiple positioning modules[J].International Journal of Control,Automation and Systems,2016,14(2):400-410.
[17]HUNG N,IM J S,JEONG S K,et al.Design of a sliding mode controller for an automatic guided vehicle and its implementation[J].International Journal of Control,Automation and Systems,2010,8(1):81-90.
[18]KIM T H,MARUTA I,SUGIE T.Brief paper:Robust PID controller tuning based on the constrained particle swarm optimization[J].Automatica,2008,44(4):1104-1110.
[19]单尧,孙永荣,黄斌,等.自主空中加油飞行对接演示平台设计与实现[J].电子测量技术,2016,39(12):176-179,188.SHAN Y,SUN Y R,HUANG B,et al.Design and implementation of a docking demonstration platform for autonomous aerial refueling[J].Electronic Measurement Technology,2016,39(12):176-179,188.
[20]张青月,王东风.基于观测器的过热汽温状态反馈控制[J].中国测试,2016,42(5):98-102.ZHANG Q Y,WANG D F.Research on observer-based state feedback control for superheated steam temperature[J].China Measurement&Testing Technology,2016,42(5):98-102.
[21]冯超,陈双叶.基于模糊控制的PAC控制器的设计[J].国外电子测量技术,2016,35(7):47-51.FENG CH,CHEN SH Y.PAC controller design based on fuzzy control[J].Foreign Electronic Measurement Technology,2016,35(7):47-51.
[22]周向阳,贾媛.航空遥感惯性稳定平台模糊/PID复合控制[J].仪器仪表学报,2016,37(11):2545-2554.ZHOU X Y,JIA Y.Fuzzy/PID compound control for inertially stabilized platform in airborne remote sensing[J].Chinese Journal of Scientific Instrument,2016,37(11):2545-2554.