二自由度SCARA机器人位置的端口受控哈密顿与反步法协调控制

针对二自由度SCARA机器人系统使用单一控制方法难以实现快速、精准的位置跟踪控制的问题,设计了基于端口受控哈密顿(PCH)与反步法的协调控制.PCH用于保证系统稳态性能,反步法用于保证系统快速性.采用指数函数作为协调函数以实现协调控制策略,从而适应二自由度SCARA机器人的轨迹跟踪控制.该SCARA机器人系统,既能够实现系统快速的跟踪位置信号,又能够提高系统的输出信号的稳态性能.仿真实验表明,当存在干扰时,采用PCH与反步法的协调控制的二自由度SCARA机器人位置跟踪系统能够有效地结合两者的优点,系统的动态性能和稳态性能优良,且能够很好地抵抗外部干扰.     

A new concept of the SCARA robot

Based on the SCARA concept, accepted worldwide, this paper considers the possibility of realizing SCARA with a full circle working area. The basis of the approach is a mechanism with two eccentrically positioned rotating discs instead several tools (hands) is also facilitated. This paper analyzes the advantages of the proposed solution and the possibilities of its realization.     

Camera assisted calibration of SCARA arms

This paper presents some experimental results obtained by applying an approach of Lenz and Tsai (1989) to SCARA arm calibration. A new camera calibration technique, which is singular-free for this type of system, is employed. Several practical recommendations are given for robot users in general and SCARA arm users in particular     

SCARA机器人内模控制方法

为了使SCARA机器人在外界干扰和模型不精确的情况下具有优良的轨迹跟踪性能,提出一种基于内模控制原理设计SCARA机器人控制器的方法。采用拉格朗日方法获得SCARA机器人动力学模型,将其作为内模控制的估计模型;选择内模滤波器[f(S)]设计内模控制器[Q(S),]使其满足稳态误差为零的条件,通过推导得出不同输入信号下的SCARA机器人控制律。通过仿真,将其与自适应模糊滑模控制方法进行对比分析,结果表明所提出的方法轨迹跟踪精度高,抗干扰能力强,控制器参数调节简单。     

球面SCARA机器人示教编程系统的研究

本文介绍我室开发的新型同ＳＣＡＲＡ机器人示教编程系统的组成，示教编程原理及提高该系统教编程精度的措施，利用该示教系统能很方便地记录各种曲面形状，用计算机显示其三维图形；将示教信息经坐标变换，可使物体的信息转化为机器人的关节控制变量。     

SCARA机器人模糊自适应滑模控制

为了提高SCARA机器人的轨迹跟踪控制性能,提出了一种基于非奇异终端滑模面和改进的快速趋近律的滑模控制策略。设计了一种非奇异的快速终端滑模面,可在任意初始状态下收敛到平衡点;改进滑模控制的趋近律,在保证快速趋近的同时可有效抑制抖振,并采用双曲正切函数代替传统的符号函数,有效地消除了高频抖振。采用模糊控制调节趋近律参数,改善初始状态误差过大时引起的力矩冲击问题;基于SCARA机器人模型仿真实验表明,实验结果跟踪性能良好,输出力矩平滑。     

SCARA based peg-in-hole assembly using compliant IPMC micro gripper

Robotic assembly is difficult as there always exist position errors between two mating parts. Compliance is added in a selective compliant assembly robot arm (SCARA) in the form of a two ionic polymer metal composite (IPMC) fingers based micro gripper. This micro gripper is integrated at the end effector position of a SCARA robot. Peg-hole interaction is analytically modeled and based on it the force required to correct the lateral and angular errors by IPMC is calculated. A proportional-derivative (PD) controller is designed to actuate the IPMC to get the desired force for correcting the peg position before assembly. Simulations and experiments were carried out by developing an IPMC micro gripper and using it to analyze various cases of peg in hole assembly. The experimental results prove that adding compliance through IPMC helps in peg-in-hole assembly.     

基于PMAC下SCARA机器人的PID参数调节

本文介绍了在使用美国Delta-Tau公司的PMAC控制卡对四轴SCARA机器人进行PID参数调节过程中所遇到典型问题，以及解决方法。     

优化深度确定性策略梯度算法

深度强化学习善于解决控制的优化问题,连续动作的控制因为精度的要求,动作的数量随着动作维度的增加呈指数型增长,难以用离散的动作来表示。基于Actor-Critic框架的深度确定性策略梯度（Deep Deterministic Policy Gradient,DDPG）算法虽然解决了连续动作控制问题,但是仍然存在采样方式缺乏科学理论指导、动作维度较高时的最优动作与非最优动作之间差距被忽视等问题。针对上述问题,提出一种基于DDPG算法的优化采样及精确评价的改进算法,并成功应用于选择顺应性装配机器臂（Selective Compliance Assembly Robot Arm,SCARA）的仿真环境中,与原始的DDPG算法对比,取得了良好的效果,实现了SCARA机器人快速自动定位。     

Extended Kalman filtering and weighted least squares dynamic identification of robot

This paper presents an experimental comparison between the weighted least squares (WLS) estimation and the extended Kalman filtering (EKF) methods for robot dynamic identification. Comparative results and discussion are presented for a SCARA robot, depending on a priori knowledge and data filtering.     

Reconfigurable Control Structure for Robots in Assembly

The increased use of changeable characteristics in modern manufacturing and robotic systems and applications call for improved system control design that offers some degree of reconfigurability. The need for control reconfiguration of robotic systems arises due to some inherent characteristics of the robotic system, variations of robot parameters due to environmental changes, major task changes typical in production changeover or manufacturing system reconfiguration, or geometry changes due to the reconfiguration of modular manipulators. In this paper, a reconfigurable controller, the Supervisory Control Switching System (SCSS), is proposed to meet the new on-line demands for changeability in robotic systems. The SCSS is capable of selecting the most suitable controller for a particular task or situation, from separate controllers designed a priori. The applicability and effectiveness of the developed switching control scheme have been illustrated through computer simulations of an AdeptOne SCARA manipulators carrying out assembly tasks.     

A PC-based open robot control system: PC-ORC

An open architecture manufacturing system pursues to integrate manufacturing components on a single platform. Therefore, a particular component can be easily added and/or replaced. In this paper, a modular and object-oriented approach for the PC-based open robot control (PC-ORC) system is investigated. A standard reference model for controlling robots, which consists of a hardware platform, an operating system module, and various application software modules, is first proposed. Then, PC-ORC system, which can reconfigure the control system in various production environments, is developed. The PC-ORC is constructed based upon the object-oriented method. Hence, it allows an easy implementation and modification of various modules. The PC-ORC consists of basic software, application objects, and additional hardware devices on a PC platform. Finally, by applying the proposed PC-ORC to a SCARA robot, the performance of the PC-ORC is examined.     

Robot dynamic calibration: Optimal excitation trajectories and experimental parameter estimation

Advanced robot control schemes require an accurate knowledge of the dynamic parameters of the manipulator. This article examines various issues related to robot dynamic calibration, from generation of optimal excitation trajectories to data acquisition and filtering, and experimental inertial and friction parameter estimation. In particular, a new method is developed for the determination of optimal joint trajectories for the calibration experiment, which is based on evolutionary optimization techniques. A genetic algorithm is used to determine excitation trajectories that minimize either the condition number of the regression matrix or the logarithmic determinant of the Fisher information matrix. All the calibration steps have been carried out on a SCARA two‐link planar manipulator, and the experimental results are discussed. © 2001 John Wiley & Sons, Inc.     

Simple LMI based learning control design

In this note, a simple linear matrix inequality (LMI) design method is proposed for iterative learning control (ILC). The design can ensure a monotonic error decay in 2‐norm. Experimental results on a SCARA robot shows that the design can achieve nearly perfect tracking. Copyright © 2009 John Wiley and Sons Asia Pte Ltd and Chinese Automatic Control Society     

模糊学习控制在SCARA机器人轨迹跟踪中的应用

模糊学习控制以模糊控制提供反馈机制为主体,辅以迭代学习控制提供前馈补偿机制,来实现对期望轨迹的完全跟踪.把模糊学习控制应用于SCARA机器人的轨迹跟踪.仿真试验表明,该方法具有简单实用、跟踪精度高、学习速度快等优点.     

一种基于思维进化算法的神经网络求解机器人逆运动学问题

研究了SCARA机器人的逆运动学问题,提出了一种采用思维进化算法来学习神经网络连接权值的方法。并将该算法成功地应用于求解机器人的逆运动学问题。计算机仿真表明,这种神经网络方法不仅具有较快的收敛速度,而且大大提高了求解的精度。     

$3C2510A的SCARA机械臂控制系统设计

在目前机械臂控制系统中,如何减小系统体积、降低系统功耗一直是传统控制方式（即“PC／工控机＋运动控制卡”）的难点。本文在对SCARA机械臂深入研究的基础上通过S3C25IOA实现了带有PCI接口的控制系统,并进行了Bootloader的移植以及PCI驱动程序的编写。     

An Efficient Algorithm for Identification of Robot Parameters Including Drive Characteristics

A procedure for estimating the dynamic model parameters of an n degree-of-freedom (DOF) robot is presented. The characteristics of the drive dynamics are included in the modelling process. In this manner, the estimated dynamic model can facilitate the design of control laws for actual implementation. Due to a regrouping procedure, the estimation model for the model parameters is formulated in an upper block triangular form. This special structure can be exploited to obtain a computational efficient estimation algorithm for the model parameters. An integral form of the estimation algorithm is then developed to eliminate the need of using joint accelerations which tend to be noisy. The complete procedure does not require prior knowledge of the manipulator's geometric parameters. Furthermore the robot manipulator needs not follow some restrictive test trajectories. The experimental results obtained from a 4-DOF SCARA robot are presented to illustrate the practical application of the method.     

Robotic assembly automation using robust compliant control

Industrial robots used to perform assembly applications are still a small portion of total robot sales each year. One of the main reasons is that it is difficult for conventional industrial robots to adapt to any sort of change. This paper proposes a robust control strategy to perform an assembly task of inserting a printed circuit board (PCB) into an edge connector socket using a SCARA robot. The task is very challenging because it involves compliant manipulation in which a substantial force is needed to accomplish the insertion operation and there are some dynamic constraints from the environment. Therefore, a robust control algorithm is developed and used to perform the assembly process. The dynamic model of the robotic system is developed and the dynamic parameters are identified. Experiments were performed to validate the proposed method. Experimental results show that the robust control algorithm can deal with parameter uncertainties in the dynamic model, thus achieve better performance than the model based control method. An abnormal case is also investigated to demonstrate that the robust compliant control method can deal with the abnormal situation without damaging the system and assembly parts, while pure position control method may cause damages. This strategy can also be used in other similar assembly processes with compliant applications.     

On the trajectory tracking control for an SCARA robot manipulator in a fractional model driven by induction motors with PSO tuning

This paper describes the fractional modeling and control of an industrial selective compliant assembly robot arm (SCARA); the fractional model was obtained by using the Euler–Lagrange and Hamilton formalisms. Each joint of the robot manipulator was driven by an induction motor. In this work, the fractional model of each induction motor was formulated, and the matching of the induction motors with the SCARA robot is shown. For comparison purposes, the SCARA robot control was formulated by conventional PI and PD and by fractional PI ^? and PD ^δ controllers. So each induction motor was controlled by using PI and fractional PI ^? controllers, and for trajectory tracking control, PD and fractional PD ^δ controllers were designed. For tuning the PI, PI ^? , PD, and PD ^δ controllers, the PSO algorithm was used; the same restrictions were used for the PI and PD classical controllers, and ITAE index was used as a cost function to be minimized. For computing the fractional derivatives and to obtain the numerical solution of the system, the Riemann–Liouville and Grünwald–Letnikov approaches were used. The numerical simulations have shown the effectiveness of the use of fractional PI ^? and PD ^δ controllers.