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《控制工程》2014,(Z1)
路径跟踪是AGV的关键技术之一,是AGV平稳高效运行的保证。单舵轮AGV是一种常见的结构形式,现有的路径跟踪算法大多复杂度较高,难以满足实际应用的需求。文中针对单舵轮AGV的运动特点及结构特征构造了运动学模型,分析了路径跟踪问题的实质。利用Lyapunov直接法,通过构造函数得到使系统渐近稳定的控制律,并且以导航传感器返回的与预定路径的误差作为输入变量,以舵角的偏转角度作为输出变量,设计出单舵轮AGV的路径跟踪控制器。考虑到车身长度与实际运动过程中AGV舵角摆动频率对控制效果的影响,在控制器中加入了模糊控制的思想。结果表明该算法简单有效,实现了AGV对路径跟踪的要求,提高了AGV的运动性能,取得了理想的应用成效。 相似文献
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路径跟踪是AGV的关键技术之一,是AGV平稳高效运行的保证。单舵轮AGV是一种常见的结构形式,现有的路径跟踪算法大多复杂度较高,难以满足实际应用的需求。文中针对单舵轮AGV的运动特点及结构特征构造了运动学模型,分析了路径跟踪问题的实质。利用Lyapunov直接法,通过构造函数得到使系统渐近稳定的控制律,并且以导航传感器返回的与预定路径的误差作为输入变量,以舵角的偏转角度作为输出变量,设计出单舵轮AGV的路径跟踪控制器。考虑到车身长度与实际运动过程中AGV舵角摆动频率对控制效果的影响,在控制器中加入了模糊控制的思想。结果表明该算法简单有效,实现了AGV对路径跟踪的要求,提高了AGV的运动性能,取得了理想的应用成效。 相似文献
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视觉AGV的差速转向控制器设计 总被引:1,自引:0,他引:1
简要地介绍了基于机器视觉导向的AGV两轮差速转向的原理和组成,并对计算机控制系统设计,图像信息识别等AGV控制问题进行了阐述,提出了一种采用模糊控制方法对AGV两轮差速转向进行控制。仿真和实验结果均表明,采用模糊控制方法对两轮差速转向进行控制,样车运行过程稳定,路径跟踪可靠,控制性能良好。 相似文献
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为了提高3C产品的自动化生产效率,以STM32F407ZGT6单片机为系统控制器核心,对磁敏传感器组寻迹的滚筒式AGV设计了16位磁敏传感器的阵列布置形式,并根据此形式以及磁导引滚筒式AVG的寻迹约束条件和行走要求提出了路径的识别与轨迹跟踪算法,即分段模糊PI控制算法,以适应AGV小车在直行 、转弯和停车三种状态下存在的位置偏差和角度偏差的控制.运用Matlab软件中Simulink模块搭建模糊控制器的仿真模型,对AGV的轨迹跟踪进行仿真,并进行了实际行走测试.AGV行驶时路径偏差保持在8 mm以内,可保证AGV稳定准确地跟踪预设路径,且具有较强的鲁棒性. 相似文献
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磁条导引方式因其成本低、路径规划灵活和抗干扰能力强而在AGV的导引控制系统中普遍使用,而磁感应信号的数据采集、控制系统结构和控制策略的设计等都是需要深入研究的问题。以差速驱动转向AGV为研究对象,以模块化、通用化设计思路为导向,给出了一种分布式磁导引AGV控制系统设计和实现方案。采用Atmega 128及外围电路作为主控单元, Atmega 16和信号调理电路为数据采集单元、HMC1021为磁条检测传感单元来设计控制器的核心硬件结构,主控单元和数据采集单元之间通过RS485通信交换数据。随后在分析和研究AGV差速驱动原理的基础上,给出了从传感到速度控制的通用模式,并且提出了查表和模糊控制相结合的通用性控制策略设计方法。软硬件测试和实验结果表明了该设计方法的可行性和有效性。 相似文献
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以单片机为系统控制器核心,针对磁敏传感器组寻迹的叉车式AGV,设计了传感器的阵列布置形式,并根据此形式以及磁导引叉车式AGV的寻迹约束条件和行走要求提出了路径的识别与跟踪算法.前进时采用分段模糊PID控制,PD系数被模糊控制器动态改变,以适应驱动轮的不同转速和前向位置偏差的大小.后退过程应用双闭环PID进行控制,姿态角和后向位置分别为内环和外环.在实际行走测试中,AGV稳定行驶时路径偏差可保持在10 mm内. 相似文献
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针对自动导向车(AGV)的路径跟踪,提出一种新的模型参考-模糊变结构滑模-PI组合跟踪控制方案。该方案将AGV设计成左右轮行走距离跟踪系统,并引进参考模型,组合了模糊控制和变结构滑模控制以及比例加积分(PI)控制。模糊变结构滑模控制提供了跟踪的快速性和稳定性,PI控制则消除稳态抖动,提高了稳态精度。仿真及实测结果表明,这种新的设计方案能达到较高的跟踪精度。 相似文献
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针对轮式移动机器人循迹偏差问题,以差速驱动型AGV为研究对象,基于LQR(LinearQuadratic Regulator)线性二次型最优控制算法设计磁导航AGV纠偏控制器,控制AGV速度实现循迹跟踪。通过对磁导航AGV偏差建模,将决定AGV运行的驱动电机线性化,建立其状态空间模型,判别系统能控、能观性;同时用Matlab进行仿真设计,实验得到最佳Q、R完成最优控制器设计;通过Simulink设计基于LQR最优控制算法的AGV纠偏控制系统模型,并与传统PID控制算法进行对比分析表明,论文设计的基于LQR算法纠偏控制模型具有更好的收敛性和实时响应性。 相似文献
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Automated guided vehicle systems (AGVSs) are used to transport goods and products in most manufacturing systems. In this research, we use a cylindrical magnet spot, which is widely used in industrial AGVSs, to develop a guidance system for indoor AGV navigation. This paper describes the navigation and control system of an AGV by magnet spot guidance with a differential drive. Furthermore, Hall-effect sensors, encoders, and counters are employed to achieve control and continuous guidance. Existing guidance methods use a gyro sensor and dead reckoning with encoders to calibrate against steering angle errors. Here, the maximum value of the magnetic flux density of the magnet spot, which is obtained by the Hall-effect sensor, is used to calibrate against steering angle errors and as a navigation guide for the AGV. Furthermore, real-time corrections for wheel-skidding errors are accomplished with a fuzzy controller. Thus, high-precision continuous guidance with stable and satisfactory navigation at high speeds is achieved. This guidance method was applied to real manufacturing processes in a ceramic plant and steel-bar reinforcement plant to examine its control ability, stability, and effectiveness. The proposed method was found to be robust to disturbances and uncertainty problems during tracking. 相似文献
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本文主要论述基于STM32的遥控小车,通过红外用NEC编码方式来控制小车,包括遥控模式和循迹模式。运动状态包括控制小车向前、向后、左转、右转、停止、变速(用PWM控制电机转速)运动。循迹模式用来模拟小车运行路径,对AGV小车的设计提供路径支持,需要用到避障模块,在检测到有物体后转向、前进一段距离再次转向,进入另一道路线,直至连续两次检测到前方有物体,小车停止。实验结果表明,小车在一定程度上可以模拟AGV小车的运行路径,搭配遥控模式,更加方便可靠。 相似文献
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This paper presents a new navigation method for an automatic guided vehicle (AGV). This method utilizes a new navigation and control scheme based on searching points on an arc. Safety measure indices are defined and are generated from the output of a fuzzy neural network which define the actions the AGV is to take when in the presence of obstacles. The proposed algorithm integrates several functions required for automatic guided vehicle navigation and tracking control and it exhibits satisfactory performance when maneuvering in complex environments. The automatic guided vehicle with this navigation control system not only can quickly process environmental information, but also can efficiently avoid dynamic or static obstacles, and reach targets safely and reliably. Extensive simulation and experimental results demonstrate the effectiveness and correct behavior of this scheme. © 2004 Wiley Periodicals, Inc. 相似文献
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《Robotics and Autonomous Systems》2014,62(9):1241-1247
This paper presents positioning improvement of a laser navigation system (LNS) using the unscented Kalman filter (UKF) and fuzzy inference system (FIS) for an automatic guided vehicle (AGV). The existing AGVs mainly used a magnetic system or an inductive system as a guidance system. However, those systems have high initial facility cost and are difficult to maintain according to changes of environment, and it can drive only the designated path by sensors which are installed on. The laser guidance system is developed to solve these problems, but it also has limitations which are slow response time and low accuracy. Therefore, we propose a sensor fusion method for the AGV. The sensors used in this paper are encoders, a gyro and the LNS, and they are fused by the UKF and FIS. To analyze the performance of the proposed system, we designed a fork-type AGV for ourselves and performed the experiment that was repeated 10 times under the same working conditions. In experimental results, we verified that the proposed method could improve positioning accuracy of the LNS effectively. In addition, it was appropriate to apply a real AGV system for autonomous driving. 相似文献