Computed force and velocity control for spatial multi-DOF electro-hydraulic parallel manipulator

A novel dynamic trajectory tracking controller for spatial 6-DOF electro-hydraulic parallel manipulator considering system nonlinearity-computed force and velocity controller is proposed, with a view of improving the control performance with high computational efficiency of control algorithm. The dynamic model of electro-hydraulic parallel manipulator, both mechanical and hydraulic system, is described by using Kane and hydromechanics method. The requisite system states are estimated via forward kinematics based upon global Newton–Raphson with monotonic descent algorithms under the measured actuator position. The desired leg position and velocity required for the proposed controller are calculated by an analytical method corresponding to the desired generalized pose, and the desired driven force is computed with an effectively simplified inverse dynamics. Under feed-forward of the desired driven force and velocity, the computed force and velocity controller is developed with actual leg position as its feedback only, and the desired leg position, velocity and driven force as its input. The control performance of the proposed controller for multi-DOF parallel manipulator is evaluated in theory and experiment, especially for dynamic tracking performance. Experimental results show that the presented controller can greatly improve the dynamic trajectory tracking performance for high real time electro-hydraulic parallel manipulator.     

采用单目视觉的无人机自动空中加油仿真

自动空中加油是未来无人机(UAV)需具备的重要能力之一。建立了包括UAV和加油机模型、视觉传感器、气动影响及视景的飞行硬管式无人机自动空中加油仿真系统;研究了单目视觉特征点识别与位姿估计算法,考虑大气扰动及加油机尾流的影响;设计了通过轨迹跟踪实现UAV与加油管会合对接的控制策略,并对加油末段的对接机动进行了仿真。结果表明,单目视觉可实现精确的相对位置测量,轨迹跟踪控制器超调量小,保证了自动空中加油的平稳对接。     

基于激光视觉传感器的机器人实时焊缝跟踪方法

为实现变姿态焊接过程的实时焊缝跟踪,提出基于机器人坐标系下绝对焊缝轨迹的实时跟踪算法。将线式激光传感器安装在机器人的法兰盘上,且位于焊枪运行的前方。焊接过程中,激光传感器连续采集焊缝位置信息,并结合手眼标定矩阵以及机器人实时姿态,将传感器采集的焊缝坐标转换到机器人基础坐标系下,从而形成空间绝对焊缝轨迹;再根据焊枪的当前位置与焊缝的空间绝对轨迹生成位置偏差。为了提高计算精度,提出采用三次非均匀有理B样条进行数据插值和检索;最后,将位置偏差变换到焊枪工具坐标系下进行实时修正。实验结果表明:该跟踪算法能够实现焊接机器人针对变姿态焊接过程的连续跟踪,跟踪过程平滑光顺,跟踪整体精度优于0.5 mm。基本满足焊缝实时跟踪应用的一般要求。     

管道焊接激光视觉跟踪的定位方法研究

为解决在管道自动焊接过程中V型坡口的识别定位问题,提出了一种基于激光视觉传感的局部区域内分步式定位方法。首先建立模板匹配,利用模板匹配方式获取焊缝初始位置区域;然后采用阈值分割和边缘提取获得激光条纹边缘线,通过Shi-Tomasi算法对边缘线进行角点检测,得到边缘线上的亚像素角点位置坐标;最后采用最小二乘法拟合得到精确的边缘直线,对上下边界线求平均值提取激光条纹的中心线,求取直线的交点得到坡口轮廓的拐点信息。通过对实际焊接现场拍摄的50幅同一高度不同位置的图像进行检测,结果表明,分步式定位方法抗干扰性强,精度较高,为完成整个跟踪自动焊接过程奠定了基础。     

移动机器人全局轨迹跟踪的自适应滑模控制

讨论了两驱动后轮角速度为控制输入的移动机器人轨迹跟踪问题，针对含有未知参数的非完整移动机器人运动学模型．基于反演（backstepping）控制算法的思想设计了变结构控制的切换函数，并由此构造了具有全局渐近稳定的白适应滑模轨迹跟踪控制器。该方法设计过程简单并具有直观的稳定性分析，适用于移动机器人的全局轨迹跟踪控制。仿真结果表明了该方法的有效性和正确性。     

基于3D激光扫描传感器的焊缝区域跟踪方法设计

一般二维数据传感器在智能焊接领域应用中,跟踪焊缝区域时,焊接枪抖振会导致跟踪误差大的问题,提出基于3D激光扫描传感器的激光焊缝自动跟踪方法,应用3D激光扫描传感器获取到完整的激光焊缝3D位置数据。对采集到的焊缝位置信息展开全局最优解处理,提取激光焊缝的相关特征。对激光焊缝跟踪相关的距离特征进行分类处理:设计模糊跟踪算法,利用基本论域方法建立目标边缘特征模型,调整激光焊缝隶属度参数,实现目标融合特征分类。在激光焊缝特征分类的基础上,利用变论域理论提高焊接跟踪控制准确率和焊缝成形检测效率,完成焊缝区域的控制跟踪,实现无人化焊接。实验结果表明:这种方法在减小跟踪误差中有明显的效果。     

A feedforward controller by modified series approximation

A new pole-zero cancellation technique using a modified series approximation is proposed for the feedforward controller. The gain of the system with the proposed feedforward controller is close to 1 for up to relatively high frequency. The tracking error of this method depends on the pth-order difference of the desired trajectory. The method is effective when the closed-loop system has unstable zeros in the left-half plane of the z plane close to the unit circle. The tracking errors are analyzed in terms of the location of an unstable zero and the reference trajectory. The effectiveness of the proposed method is shown in the simulation     

基于改进TLD算法的激光视觉传感型焊缝跟踪

为了解决基于线激光视觉传感的焊缝中心位置定位精度不高的问题, 采用了一种基于改进跟踪-学习-检测(TLD)算法的焊缝跟踪方法。由激光视觉传感器实时获取焊缝图像, 采用将跟踪器与检测器结合的TLD算法实时跟踪焊缝特征点, 同时通过在线学习机制更新分类器参量。在此基础上对激光条纹图像截取感兴趣区域, 大幅减少检测器的搜索区域; 根据激光条纹光强分布特性, 结合纠偏方向选取跟踪器有效特征点, 以此提高算法效率, 对不锈钢板V型焊缝和搭接焊缝进行跟踪试验。结果表明, 跟踪与检测可实现共同定位焊缝中心位置, 其融合的焊缝跟踪方法能够准确地提取焊缝特征点, 两种焊缝跟踪平均绝对误差分别为0.062mm和0.052mm。此方法为提高焊缝跟踪精度提供了依据。     

激光视觉焊缝跟踪实时图像处理研究

对激光视觉传感焊缝跟踪实时图像处理的方法进行了研究，就其中的关键技术-激光带中心的抽取和特征点的检测提出了切实可行的方法。该处理方法效果好，处理速度快，能够满足跟踪系统的实时性要求。     

一种基于激光视觉的焊缝实时检测技术研究

提出了一种基于激光视觉的焊缝实时检测技术,旨在提高焊缝检测的速度和精度。在实际的焊接过程中,由于大量噪声的干扰,焊接图像的采集一直是一个复杂的过程。 本文首先建立基于激光视觉的检测系统,以获得激光条纹的原始图像。在此基础上,将原始激光条纹图像灰度化,并提出一种改进的快速中值滤波算法,在去除图像中椒盐噪声的同时,缩短了程序运行时间。并通过Otsu阈值分割获得激光条纹的二值图像,提取感兴趣的激光条纹区域。接着结合方向模板法和脊线跟踪法提取激光条纹中心线,最后采用亚像素级角点法提取焊缝的特征点。 实验证明,本文提出的方法有效地克服了焊接环境的影响,不仅缩短了焊缝特征点检测的时间,而且具有较高的检测精度,符合实际焊接要求。     

双光束激光双路焊接的跟踪控制技术研究

为了实现对T型接头的双光束激光焊接,采用基于多轴联动数控机床的双光束激光焊接平台和基于视觉传感器的焊缝跟踪控制相结合的方法,进行了理论分析和实验研究.通过建立平台的运动学模型实现了焊缝的轨迹规划,设计了基于比例、积分、微分控制的位置环和高速焊接过程中的跟踪算法来提高控制系统的控制精度等,并且通过焊接试验,验证了所提出的算法.结果表明,该焊接跟踪控制系统能够快速、准确地对焊接过程中的偏差进行动态补偿,很好地完成了对T型接头的双光束焊接.     

Fuzzy sliding-mode control of a human arm in the sagittal plane with optimal trajectory

Patients with spinal cord injuries cannot move their limbs using their intact muscles. A suitable controller can be used to move their arms by employing the functional electrical stimulation method. In this article, a fuzzy exponential sliding-mode controller is designed to move a musculoskeletal human arm model to track an optimal trajectory in the sagittal plane. This optimal arm trajectory is obtained by developing a policy for the central nervous system. In order to specify the optimal trajectory between two points, two dynamic and static optimal criteria are applied simultaneously. The first dynamic objective function is defined to minimize the joint torques, and the second static optimization is offered to minimize the muscle forces at each moment. In addition, fuzzy logic is used to tune the sliding-surface parameter to enable an appropriate tracking performance. Simulation results are evaluated and compared with experimental data for upward and downward movements of the human arm.     

Hysteresis modeling and tracking control for a dual pneumatic artificial muscle system using Prandtl–Ishlinskii model

This study investigated pressure/length hysteresis characteristics. Instead of the conventional force/length hysteresis model, a Prandtl–Ishlinskii (P–I) model of a dual pneumatic artificial muscle (PAM) system is presented. For the comparison, an alternative hysteresis model such as Bouc–Wen (B–W) model is also considered. All model parameters are identified by real code genetic algorithm (RCGA). Different feedback control strategies are combined with a feed-forward controller based on a P–I model for hysteresis compensation to reduce the tracking error of the dual PAM system. The experimental results validated the use of the proposed controller for trajectory tracking of PAM systems.     

Trajectory planning for the tracking control of systems with unstable zeros

In this paper, a trajectory control strategy for a nonminimum phase system is proposed. A continuous-time version of the zero-phase error-tracking controller (ZPETC), a well-known discrete-time feedforward controller for tracking control of a nonminimum phase system, is derived. The performance of the continuous ZPETC is further enhanced by adopting a specially designed sinusoidal trajectory to compensate gain error. The sinusoidal trajectory has a synergic effect on tracking performance when combined with the continuous ZPETC. The effectiveness of continuous ZPETC with sinusoidal trajectory is confirmed through simulation and experiment of a nonminimum phase plant, a single link flexible arm.     

基于Canny检测算法实现的目标跟踪

为了设计一种实时高效、稳定可靠的图像目标跟踪系统平台,避免因图像边缘提取效果差而引起跟踪失败,采用自适应Canny边缘检测算法。该自适应算法能够很好的确定平滑参数以及高、低两个阈值,更好的获得图像边缘图。经Canny算法处理图像目标后,获得目标的单像素边缘图,根据边缘图计算得到目标质心。利用最小二乘法拟合出目标的运动轨迹,同时可根据时间间隔预测出目标质心的下一位置,控制伺服机构,实现目标跟踪。实验表明,采用Canny算法的目标跟踪系统,能够满足实时跟踪的需要。     

位移矢量一致下的多飞行器三维轨迹跟踪识别

合作靶标点三维轨迹的跟踪识别是实现室内环境中多飞行器位姿估计的关键,为此,提出了一种基于时空一致条件下的多目标三维轨迹跟踪识别算法。该方法包括运动轨迹跟踪与识别两部分,对于合作靶标点三维轨迹跟踪,提出了一种基于运动目标位移矢量一致的数据关联方法,该方法首先利用运动平滑性假设计算得到的数据关联概率值,结合匈牙利算法求解得到目标的数据关联关系,然后在贝叶斯滤波框架下实现合作靶标点的三维轨迹跟踪。对于合作靶标点的三维轨迹识别,又可以分为粗细两部分,利用运动轨迹Hankel矩阵的秩实现运动轨迹的粗识别,利用运动轨迹之间的Hausdorff距离实现运动轨迹的细识别,最终实现对每一个飞行器的轨迹识别与注册。实验结果表明,在三维测量手段为机器视觉,测量空间大小为2 m×2 m×2 m,提出的多目标跟踪算法的三维轨迹跟踪误差小于4 mm（3σ）时,轨迹识别正确率为100%。因此,所提出的算法可以有效地实现多飞行器上合作靶标点三维轨迹的跟踪识别。     

Design of M-G modal space sliding mode control for lower limb exoskeleton robot driven by electrical actuators

Lower limb exoskeleton robot (LLER) can help patients with lower limb paralysis to carry out effective rehabilitation training. However, LLER is a kind of nonlinear system with the strong dynamic coupling between joints and the parameter perturbation following different poses of the robot. They will damage the control performance in the process of trajectory tracking. To solve these problems, a novel control strategy, Mass-Gravity modal space sliding mode control (M-GMSSMC), is proposed. The objective for this paper is to develop a novel decoupling control framework for an electrical actuators driven LLER to track a predefined gait trajectory. The controller design aims to improve trajectory tracking accuracy, reduce dynamic coupling between hip joint and knee joint and weaken the chattering phenomenon of the sliding mode controller. The decoupling condition and the robust stability condition are analyzed in this work. Experimental results validate the correctness of the presented conclusions and show the effectiveness of the proposed M-GMSSMC.     

轮式机器人滑模轨迹跟踪控制器设计

轮式机器人是一个典型的非完整性系统。由于非线性和非完整特性,很难为移动机器人系统的轨迹跟踪建立一个合适的模型。介绍了一种轮式机器人滑模轨迹跟踪控制方法。滑模控制是一个鲁棒的控制方法,能渐近的按一条所期望的轨迹稳定移动机器人。以之为基础,描述了轮式机器人的动力学模型并在二维坐标下建立了运动学方程,根据运动学方程设计滑模控制器,该控制器使得机器人的位置误差收敛到零。     

Robust Smooth-Trajectory Control of Nonlinear Servo Systems Based on Neural Networks

The electromagnetic torque introduces ripples into the electromechanical motion system due to nonlinearities, such as uncertain changes of magnet field, load, and friction, which generate speed oscillations and deteriorate the tracking performance of servo system. Furthermore, the minimum time response and smooth trajectory tracking are cruces in servo control. In this paper, an available method is proposed to solve them by using neural networks (NNs) and a nonlinear smooth trajectory filter (STF) for the robust smoothing feedforward control of a class of general nonlinear systems. First, the online weight-tuning scheme based on Lyapunov function can guarantee the boundedness of tracking error by good performance of NNs modeling nonlinear functions. Second, a feedforward controller based on the output of nonlinear STF is designed to guarantee minimum time response and smooth trajectory tracking. Finally, as a example, the motion system can be equivalent to the two-order system under the linear closed-loop current control in view of the (d,q) mathematic model for PM synchronous motor, so that this robust smoothing control method using neutral networks can be applied into position servo control. Moreover, the validity and effectiveness of this control method are verified through simulations and experiments     

基于CMOS摄像头的智能车路径跟踪系统设计

设计了一种能自动识别和跟踪路径的智能车系统。用以MC9S12XS128作为核心控制器,利用COMS图像传感器OV6620作为路径信息采集装置,通过对采集图像进行二值化处理、去噪操作、边缘检测和断点修补后提取出路径中心信息。利用最小二乘法对路径中心信息进行直线拟合,根据拟合直线的参数计算舵机控制量。对舵机采用PD控制算法,根据舵机转向角设定小车的速度,并对小车实行转角和速度的实时控制。实验证明,该智能车系统能够沿着黑色赛道快速稳定地自动行驶,实现了路径识别与跟踪。