改进狼群算法的SCARA机械臂自适应迭代学习控制

针对减小机器人重复运动的位置、速度跟踪误差的问题,给出一种基于狼群算法优化的机械臂自适应迭代学习控制策略。根据SCARA(Selective compliance assembly robot arm)机械臂驱动方程,设计动力学系统的迭代学习控制律。引入自适应步长的狼群算法,使狼群能够根据猎物气味浓度动态调整移动步长,提高了算法的收敛速度和精度。该策略对机械臂控制器参数KP、KD进行寻优时,得到了良好的控制效果,实现了对期望轨迹的有效跟踪。实验结果表明,该算法灵活性好,对系统期望轨迹具有较高的跟踪精度,有效降低了双关节机械臂的位置、速度跟踪误差,具有较强的可行性与有效性。     

伪目标迭代生成的机器人误差补偿算法

针对机器人误差模型建立后的误差补偿问题,提出一种改进的伪目标迭代算法。该算法用每次迭代中生成新的伪目标来修正关节角,从而不断减小机器人实际误差。完善了伪目标迭代算法流程,提出了5种新的不同的伪目标生成方法,分析了各种方法的特点和适用场景。结合多种伪目标生成方法提出了一种集成算法,进一步提高误差补偿精度。使用HSR-JR612机器人进行仿真实验,仿真结果表明,算法耗时在毫秒级别,补偿效果好,集成算法能进一步提高位姿补偿效果。最后使用UR10机器人与激光跟踪仪进行实验,实验结果表明,补偿后机器人末端位置误差可以减小到0.06 mm以内,姿态误差可以减小到0.025°以内。     

基于机构精度通用算法的机器人位姿误差分析

在Denavit-Hartenberg参数法建立的机器人末端位姿变换方程的基础上,利用机构通用精度算法建立了机器人末端位姿误差模型。通过矩阵运算,建立了机器人末端位姿误差与各杆件运动学参数误差之间的函数关系式。在SCARA机器人上的实验表明,用此方法建立的误差模型进行误差标定和补偿,可以提高机器人的定位精度。     

基于迭代学习控制的电液机床工作台控制方法研究

鉴于传统机床加工零件时工作台进给动作具有重复运动的特点,该文为了实现工作台高精度位置伺服控制,提出了一种基于迭代学习控制算法,用于解决机床工作台位置控制误差。首先,以组合数控机床为研究对象,介绍并建立数控机床工作台位置伺服系统数学模型;然后针对工作台位置伺服系统设计迭代学习控制算法框架;最后搭建数控机床工作台位置伺服实验平台,用不同控制信号对迭代学习控制算法和传统的PID算法进行对比实验。实验结果显示,基于迭代学习控制算法有效地降低了机床工作台控制误差,为数控机床高精度进给运动提供参考。     

基于迭代学习的电液机械手末端轨迹跟踪控制研究

针对目前常见串联式机械手末端存在控制误差累计而导致末端控制精度较低,无法实现高精度位置伺服控制,使得末端轨迹跟踪控制较差等问题,该文借助迭代学习控制算法的优点,提出了一种基于迭代学习的电液机械手末端轨迹跟踪控制算法。首先,该文以型号为REbot-6R机械手为研究对象,建立机械手的三维模型和坐标,利用D-H坐标,建立REbot-6R机械手运动学模型;然后,设计了基于迭代学习的电液机械手末端轨迹跟踪控制器;最后,以REbot-6R机械手为对象搭建实验平台进行轨迹跟踪控制实验。实验结果表明了迭代学习算法能够很好的运用在REbot-6R机械手上,有效性地解决机械手末端轨迹跟踪控制较差等问题,提高了轨迹跟踪精度。     

扩展卡尔曼滤波和配准算法的工业机器人误差补偿

针对现有工业机器人误差,特别是工业机器人末端轨迹精度低、实时监测计算复杂等问题,提出利用扩展卡尔曼滤波器和配准算法组合提高机器人末端轨迹精度的算法,解决了机器人末端精度低、控制补偿不准确等问题。建立SCARA机器人数学模型,同时建立基于扩展卡尔曼滤波和配准算法的机器人误差补偿模型,通过扩展卡尔曼滤波、配准算法进行误差补偿,实现了末端精度的提高。通过仿真验证,分析对比机械手末端轨迹补偿前后的误差,证明了算法的可靠性与准确性。     

基于自然手势交互的工业机器人示教系统设计与实现

提出一种基于自然手势交互的工业机器人示教方案,用Leap Motion传感器采集手部数据,将手掌坐标动态映射到机器人手臂坐标系统中,控制机机器人手臂跟随手掌位置实时运动,同时通过聚类算法识别出手势类型,控制末端夹具实现抓取、放置、停止等动作。进一步以爱普生SCARA机器人为基础搭建了自然手势示教实验平台,实验结果表明示教效果良好,误差在允许范围内。     

线驱动机器人P-PID控制算法研究

由于线驱动机器人采用绳索传动,而绳索具有一定的弹性,增加了控制的难度。为了提高线驱动机器人的控制精度,提出了一种P-PID控制算法,弥补了电机回程时由于绳索弹性产生的误差。基于六自由度线驱动机器人进行实验证明该算法的有效性。实验结果表明,相比于传统的PID控制算法,该算法有效地降低了绳索传动时的回程误差,提高了机器人的末端控制精度。     

基于血糖平衡调节机制的串联机器人运动调控方法

针对串联机器人关节处移动位移、转动角度对末端位置精度的影响问题,提出一种基于生物学血糖平衡调节机制(BGBAM)的串联机器人运动调控方法。通过分析BGBAM的调控机理和生物学数学模型,建立串联机器人末端位置精度调控模型。以HSR-SR3400机器人为研究对象,推导机器人末端位置和沿y轴方向的位置误差调控模型,最后进行了仿真实验和精度调控方法对比实验。实验结果表明,基于BGBAM的调控方法减小了机器人关节处位移、角度误差对其末端位置的影响程度,提高了机器人末端位置精度。     

双工业机器人不同约束下协同运动轨迹规划

针对双工业机器人协作过程中的轨迹规划问题,对IRB200机器人进行建模,并求解机器人的正逆运动学。结合求解的正逆运动学提出紧约束下耦合运动和松约束下叠加运动算法。紧约束将机器人末端执行器之间建立不变的约束关系,实现机器人末端执行器之间产生耦合运动;松约束将机器人末端执行器之间建立随时间变化的约束关系,实现机器人末端执行器之间产生叠加运动。最终在MATLAB中分别进行协同搬运、协同绘制“铜钱”仿真实验验证算法,从姿态图、轨迹图及从机器人理论位置和实际位置对比能够看出,在不考虑机械误差、标定误差及机器人制造误差的情况下能够满足相关任务要求,实现从机器轨迹的自适应规划,避免对双工业机器人分别进行轨迹规划。     

Improving tracking performance of industrial SCARA robots using a new sliding mode control algorithm

This paper addresses the implementation of a new sliding mode control algorithm for high speed and high precision tasks, which is robust against variations in the robot parameters and load. The effects of nonlinear dynamics, which are difficult to model accurately, become prominent in high speed operations. This paper attempts to treat the nonlinear dynamics of a SCARA robot as a disturbance. Based upon this approach, a new sliding mode control algorithm is proposed, in which a switching control input can be obtained easily and is determined to satisfy the existence condition for sliding mode control. A graphic simulator is used to evaluate the proposed algorithm for a SCARA robot. Simulation results show that the proposed algorithm is robust against disturbances and can reduce the magnitude of chattering, which is an unavoidable problem in sliding mode control. Experiments are carried out to validate the simulated results with an industrial SCARA robot using DSPs.     

Implementation of a robust dynamic control for SCARA robot

A control system for SCARA robot is designed for implementing a robust dynamic control algorithm. This study focuses on the use of DSPs in the design of joint controllers and interfaces in between the host controller and four joint controllers and in between the joint controllers and four servo drives. The mechanical body of SCARA robot and the servo drives, are selected from the commercially available products. The four joint controllers, assigned to each joint separately, are combined into a common system through the mother board hardwarewise and through the global memory softwarewise. The mother board is designed to connect joint controllers onto the board through the slots adopting PC/104 bus structures. The global memory stores the common data which can be shared by joint controllers and used by the host computer directly, and it virtually combines the whole system into one. To demonstrate the performance and efficiency of the system, a robust inverse dynamic algorithm is proposed and implemented for a faster and more precise control. The robust inverse dynamic algorithm is basically derived from an inverse dynamic algorithm and a PID compensator. Based upon the derived dynamic equations of SCARA robot, the inverse dynamic algorithm is initially implemented with l msec of control cycle—0.3 msec is actually used for the control algorithm—in this system. The algorithm is found to be inadequate for the high speed and precision tasks due to inherent modelling errors and time-varying factors. Therefore a variable PID algorithm is combined with the inverse dynamic algorithm to reinforce robustness of control. Experimental data using the proposed algorithm are presented and compared with the results obtained from the PID and the inverse dynamic algorithms.     

大范围平动并联机器人运动学解耦与速度自适应规划

并联机器人是一种多支链、多关节、强耦合非线性系统,具有高速、高刚度和大负载等明显优势而被广泛应用到工业领域.然而,随着关节数量的增加导致该类机器人运动学解耦和高精度平稳控制的难度较大.为实现大范围平动3-RRRU并联机器人自动化轨迹跟踪和控制的平稳性,针对运动学解耦和速度自适应规划方法展开了系统、深入地研究.首先,应用...     

沿任意倾斜面的机器人力/位置控制方法研究

设计了沿任意倾斜面的机器人自适应阻抗控制方法,该方法解决了接触面法向方向、环境阻尼、刚度参数未知对机器人力/位置控制的影响问题。在机器人与倾斜面碰撞接触过程中采用递归最小二乘(RLS)算法估计环境的阻尼、刚度,根据接触力矩实际值与期望值的偏差实现机器人末端期望姿态的调整;在机器人末端沿倾斜面滑动阶段,设计规则自调整的模糊控制器,根据机器人末端位移、接触力误差实时调整机器人阻抗控制模型参数,以适应环境阻尼、刚度的变化。提出的控制方法具有编程实现简单且对环境参数变化鲁棒性较强的优点,实验验证了控制方法的有效性。     

Design of a fuzzy-sliding mode controller for a SCARA robot to reduce chattering

To overcome problems in tracking error related to the unmodeled dynamics in the high speed operation of industrial robots, many researchers have used sliding mode control, which is robust against parameter variations and payload changes. However, these algorithms cannot reduce the inherent chattering which is caused by excessive switching inputs around the sliding surface. This study proposes a fuzzy-sliding mode control algorithm to reduce the chattering of the sliding mode control by fuzzy rules within a pre-determined dead zone. Trajectory tracking simulations and experiments show that chattering can be reduced prominently by the fuzzysliding mode control algorithm compared to a sliding mode control with two dead zones, and the proposed control algorithm is robust to changes in payload. The proposed control algorithm is implemented to the SCARA (selected compliance articulated robot assembly) robot using a DSP (digital signal processor) for high speed calculations.     

一种改进的SCARA机器人动力学参数辨识方法

针对SCARA机器人动力学参数辨识问题,提出了一种基于优化改进傅里叶级数的辨识方法。根据SCARA机器人完整动力学方程,推导得到动力学模型的线性形式。采用改进傅里叶级数作为机器人关节的激励轨迹,使得关节角度满足连续周期性,并且关节角速度和角加速度在轨迹起始和停止时刻为零。为进一步提高辨识精度,以SCARA机器人观测矩阵的条件数为目标函数,采用基于排挤机制的小生境遗传算法对激励轨迹的系数进行优化。考虑到测量噪声的影响,采用加权最小二乘法（WLS）作为参数估计方法。实验结果表明,采用所提方法能准确辨识出SCARA机器人的动力学参数,两关节力矩测量值和预测值的残差均方根分别减小了11.50%和26.35%。     

Implementation of robust adaptive control for robotic manipulator using TMS320C30

A new adaptive digital control scheme for the robotic manipulator is proposed in this paper. Digital signal processors are used in implementing real time adaptive control algorithms to provide an enhanced motion for robotic manipulators. In the proposed scheme, adaptation laws are derived from the improved Lyapunov second stability analysis based on the adaptive model reference control theory. The adaptive controller consists of the adaptive feedforward and feedback controller and PI type time-varying control elements. The control scheme is simple in structure, fast in computation, and suitable for implementation of real-time control. Moreover, this scheme does not require an accurate dynamic modeling, nor values of manipulator parameters and payload. Performance of the adaptive controller is illustrated by simulation and experimental results for a SCARA robot.     

插接管道焊缝扫查机器人的位置/力控制

为了使机器人的超声探头能够紧密贴合被检管道表面,设计了一种被动柔顺性末端执行器,并提出了一种被动关节与主动关节分离的外环混合位置/力控制策略,进行了位置/力控制仿真。确定了被动柔顺性末端执行器微动位置调整与主动关节输出变量之间求解关系,建立了理想状态下的准静态力学控制模型,理论上证明了位置偏差和力偏差均可通过主动关节的控制得到有效消除,保证控制精度。仿真研究了分度角分别为0、30°、60°与90°所对应的圆、椭圆及直线的截面线轨迹扫查情况。结果表明在各种情况下的位置与力控制都收敛并满足精度要求,从而证明了所提出的被动柔顺关节外环位置/力控制策略是有效的。     

A novel curvature circle iterative algorithm for contour error control of multi-axis CNC machine tools

High-precision real-time estimation of contouring errors is a prerequisite for contouring errors control of multi-axis CNC machine tools. This paper focuses on developing a nearest point projection curvature circle iterative (NPP–CCI) algorithm to achieve real-time estimation of multi-axis contouring errors. It is found that the traditional curvature circle iterative (CCI) method has two major shortcomings. The first is that the iterative process may terminate incorrectly at the local contour position, and the other is that the actual tool position and local curvature circle are not necessarily coplanar in three-dimensional space, which would lead to inaccurate calculation of the delay time parameter and eventually affect the estimation accuracy. In order to address the problem of false termination, an index method is used to find the closest reference position with respect to the actual position. At the same time, the projection technology is proposed to overcome the problem met in extending the planar curvature circle iterative method to the spatial applications. The proposed NPP-CCI algorithm is more suitable for spatial contouring errors estimation in tracking complex trajectories and has higher estimation accuracy than the traditional CCI algorithm. Various experiments with different tool paths are conducted on an in-house developed multi-axis experimental platform to verify the effectiveness of the proposed algorithm. The experimental results show that the NPP-CCI algorithm can estimate the contouring errors with higher accuracy than the traditional CCI algorithm, and with the help of real-time computation and compensation, the contouring errors are reduced by more than 44% in terms of the MAX and RMS values.     

基于位姿反馈的三臂空间机器人抓捕轨迹规划

以三臂空间机器人为研究对象,针对经历奇异位形时出现的位姿误差问题,提出一种基于位姿误差反馈的轨迹规划算法。根据系统一般运动学方程并结合动量守恒方程建立系统运动学模型,利用位姿期望指令得到误差运动方程。以关节角速度为控制量,设计了基于位姿误差反馈的控制率,使闭环系统的跟踪误差按指数速度收敛。该方法能够减小机器人奇异点邻域内的位姿跟踪误差,且在离开奇异区域后能完全消除误差。仿真结果证明了该方法的有效性。