双关节机器人操作臂控制系统设计

本设计针对工业现场使用的双关节机器人,主要完成了硬件系统平台构建和软件系统的设计。应用单片机技术,设计一款主从操作的控制器,能够根据旋转编码器的控制指令精确的控制电机的速度、位置、正反转等物理量,从而满足机器人操作臂精确位置伺服驱动的要求。     

基于FuzzyP的多臂机器人机械臂控制系统设计

机械臂是多臂机器人的重要组成部分,针对基于姿态识别控制及位置识别控制系统受到被控量振荡影响,而导致机械臂运动轨迹控制不精准的问题,提出了基于FuzzyP的多臂机器人机械臂控制系统设计;基于FuzzyP控制系统,找到系统控制平衡点,设计系统硬件结构包含3个机械臂,共十八个自由度,简化关节控制器连线,选择直流有刷电机,采用增量型编码器,设计H桥电路,配合74ACT244增强驱动电路,利用NRF24L01无线模块获取与处理位置信息;使用FuzzyP控制器,抑制被控量振荡,控制连杆运动,完成多臂机器人机械臂控制方案设计;由实验结果可知,该系统轨迹与预期轨迹基本一致,较好解决多臂机器人机械臂对接精确定位要求。     

具有轨迹约束的操作臂避障

该文提出一种基于多Agent的操作臂控制算法,借助于拟合度的概念,使操作臂末端点沿任一给定轨迹运行,进而可以实现避障功能。     

6维矩阵及操作臂的运动学动力学

本文应用6×6转换阵,6维铰基矢阵导出操作臂雅可比阵,并应用子系统牛顿欧拉递推法解出了带回路操作臂的动力学.具有方程数少,递归及程式化计算,易于工程应用,便于推广到解复杂机器人运动学、动力学.并以5杆回路操作臂为例作了程式化计算.     

基于神经网络的机械臂的力控制方法

本文提出一种基于神经网络的力控制方法,由两个串联的神经网络构成机械臂的力控制器,其中一个网络用来学习机械臂本身的逆动力学系统,而另一网络用来学习未知的被接触环境的动力学特征,这种方法避免了困难的接触环境建模问题。一个 双连杆机械臂的力控制的仿真实验描述了种种方法的有效性。     

机械臂的动态混合控制

本文研究当机械臂的终端受有约束时的控制问题,其中心内容是给出“任务规范投影算子”的概念,利用它首先将机械臂的动态方程解耦为两组方程,它们分别描述了运动与约束力,在此基础上给出了机械臂的控制律,使闭环系统跟踪期望的速度与约束力。     

带可伸缩操作臂的球形机器人的研制

针对目前球形机器人不具备操作能力的不足,介绍了一种带有可伸缩操作臂的新型球形移动机器人BYQ-IV,对该机器人的机械结构进行了详细的描述和分析,并给出了无线分布式的机器人运动控制系统和基于adhoc 网络的人机无线通信系统,提出了基于状态反馈的运动控制方法．最后,通过对样机的实验分析验证了该设计和控制方法的有效性．     

机器人操作臂跟踪动态目标的轨迹规划方法

针对机器人操作臂跟踪运动目标问题,提出一种基于遗传算法的轨迹规划方法。通过对关节加速度的增量进行编码,实现在操作臂的关节空间进行轨迹优化,得到操作臂在跟踪运动目标过程中所需要的轨迹。仿真计算的结果表明,所提出的方法是有效的。     

基于多AGENT的虚拟企业伙伴选择系统

伙伴选择是虚拟企业建立过程中的核心问题。在基于多agent的虚拟企业体系结构基础上,通过本体驱动的虚拟企业目标体系描述与分解,将虚拟企业伙伴选择问题表示为分布式约束满足和优化问题,并进一步以agent谈判的方式来求解该问题,最终得到优化的伙伴选择方案。本体驱动的虚拟企业目标描述与分解方法,为不同企业之间的谈判提供了通用词汇;用分布式约束满足和优化的方法对问题进行形式化描述,可以为企业之间的谈判提供论域和决策支持。分布式约束满足和优化方法的应用,为解决虚拟企业伙伴选择问题提供了一种新思路。     

三自由度机械臂的继电式控制

本文介绍了一个具有三个自由度机器人手臂的继电式控制器的设计方法。通过公式,表达了该机器人手臂的数学模型、继电式控制器和其电气拖动装置的特征。利用VAX11/750计算机进行继电式控制器开关时间的计算,以及手臂移动的模拟。而利用现有的M6800单板机作继电式控制器,对一台试验性机器人手臂进行了实际的控制试验。这台试验性机器人手臂同数学模型机是相似的。这个试验,证实了实际结果同模型机器人的计算结果是相当一致的。     

并联机器人力控制算法实时并行处理

对并联机器人力控制算法基于并行结构的计算进行了研究，设计了并行处理双机系统结构。采用文中的处理方法大大提高了并联机器人力控制算法的处理速度，保证了实时力控制，进而改善并联机器人的控制质量与性能。     

Further results on adaptive iterative learning control of robot manipulators

Based on a combination of a PD controller and a switching type two-parameter compensation force, an iterative learning controller with a projection-free adaptive algorithm is presented in this paper for repetitive control of uncertain robot manipulators. The adaptive iterative learning controller is designed without any a priori knowledge of robot parameters under certain properties on the dynamics of robot manipulators with revolute joints only. This new adaptive algorithm uses a combined time-domain and iteration-domain adaptation law allowing to guarantee the boundedness of the tracking error and the control input, in the sense of the infinity norm, as well as the convergence of the tracking error to zero, without any a priori knowledge of robot parameters. Simulation results are provided to illustrate the effectiveness of the learning controller.     

Real-time shared control system for space telerobotics

The shared control system is a modular real-time system designed to execute complex tasks through the intelligent coordination of task modules. A state machine is used to control task sequencing, and due to the automatic switching, the accuracy and reliability with which tasks are executed, is greatly improved. Tasks consist of sets of independent, modular, and reusable subtasks whose outputs are combined to create the control. This system has proved itself useful for rapid development of reliable high level multiple sensor based manipulation and control tasks. Additionally, we have integrated a neural network based visual servoing system, a semi-compliant Cartesian trajectory following heuristics, and a real-time graphical user interface in the system. The shared control system was implemented for the Self-Mobile Space Manipulator (SM ²) to handle a range of tasks associated with locomotion, manipulation, and material transportation on Space-Station Freedom.     

Artificial realization of human skill for contour control of robot manipulator

A methodology for the artificial realization of expert human skill is described. Artificial human skill was realized in the problem of contour control of mechatronic servo systems including robot manipulators and machine tools. The merits of the artificial human skill thus obtained are discussed. This work was presented, in part, at the International Symposium on Artificial Life and Robotics, Oita, Japan, February 18–20, 1996.     

Adaptive Control For Robotic Manipulators Executing Multilateral Constrained Task

This paper presents a model‐based adaptive control in task coordinates for robotic manipulators executing multilateral constrained tasks The controller works based on the concept of orthogonality between force and motion in the subspaces derived from the constraints. The control gains are independently adjustable in each subspace. The friction force, depending on the contact force, is compensated adaptively. Asymptotic convergence for both force and motion tracking errors is guaranteed by the Lyapunov‐Like Lemma. Experimental results obtained using a 3 D.O.F. robot are given.     

机械手的自适应前馈补偿变结构控制及其微机实现

为了实现高速、高精度的机械手的控制,本文将自适应前馈补偿控制与变结构理论相结合,给出了一种新的鲁棒性控制方法.通过对机械手的实时控制,证明了该方法是可行的.     

A parallel fuzzy-controlled flexible manipulator using optical tip feedback

Investigation and development of a fuzzy-controlled highly non-linear two-axis manipulator with a single-flexible link using a novel patented optical tip displacement feedback is described. The controller comprises a parallel fuzzy supervisor that is used to alter the derivative term of a linear classical PD controller, which is updated in relation to the measured tip error and error rate.Implementation of the supervisory fuzzy controller is described using both serial and parallel operation on transputers.The design of the fuzzy rules was made with a modified closed-loop phase-plane method. The design approach results in a controller implementation that uses only 14 rules and is suitable for cheaper CPU-constrained and memory-challenged embedded processors.The benefits introduced by this procedure include a method to decide where and when the action takes effect in the controller and a greatly reduced rule base. The parallel operation achieved rise times of 0.033 s and settling times of 0.064 s for a payload of 0.7 kg considerably better than other workers did.An 128% increase in payload, 73.5% faster settling time and a reduction of steady-state error of over 50% were achieved using fuzzy control over its classical counterpart.     

Fuzzy sliding mode control for a robot manipulator

This work presents the design of a robust control system using a sliding mode controller that incorporates a fuzzy control scheme. The presented control law superposes a sliding mode controller and a fuzzy logic controller. A fuzzy tuning scheme is employed to improve the performance of the control system. The proposed fuzzy sliding mode control (FSMC) scheme utilizes the complementary cooperation of the traditional sliding mode control (SMC) and the fuzzy logic control (FLC). In other words, the proposed control scheme has the advantages which it can guarantee the stability in the sense of Lyapunov function theory and can ameliorate the tracking errors, compared with the FLC and SMC, respectively. Simulation results for the trajectory tracking control of a two-link robot manipulator are presented to show the feasibility and robustness of the proposed control scheme. This work was presented in part at the 13th International Symposium on Artificial Life and Robotics, Oita, Japan, January 31–February 2, 2008     

机械臂轨迹跟踪控制的仿真

该文详细讨论了刚性机械臂的动力学模型、轨道跟踪控制策略及其MATLAB的仿真.在成功建模的基础上,使用常规PD控制策略,非常好地完成了轨道跟踪控制任务.即使在模型未知的情况,仍然可以用PD直接控制跟踪目标轨迹.该文中运用了李亚普诺夫稳定性理论,对PD控制进行稳定性判定.通过对双机械臂和三机械臂的轨迹跟踪控制的MATLAB仿真,证明了控制策略的有效性.同时根据仿真结果的比较,对PD控制策略进行了鲁棒性的分析.分析结果为PD控制的鲁棒性会随着控制对象的自由度的增加而降低.