共查询到18条相似文献,搜索用时 850 毫秒
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在机器人力/位置混合控制的基础上,本文提出了一种对力控制回路采用自适应模糊控制的方法,有利于提高系统对机器人末端操纵器五外界工作环境接触时,其接触刚度不确定性的自适应能力,仿真结果表明,该控制方法与常规PID控制相比,系统的自适应能力和鲁棒性有显著的改善。 相似文献
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自适应模糊与CMAC并行的机器人力/位置控制 总被引:2,自引:1,他引:1
为提高机器人系统对机器人末端操纵器与外界工作环境接触时,其接触刚度不确定性的自适应能力,在机器人力/位置混合控制的基础上,设计出了一种基于自适应模糊与CMAC并行控制的机器人力控制器,采用小脑模型神经控制器实现前馈控制,实现被控对象的逆动态模型,自适应模糊控制器实现反馈控制,保证系统的稳定性,且抑制扰动。以平面两关节机器人进行仿真,仿真结果表明,系统的自适应能力和力跟踪能力有显著的提高,机械手在其末端操纵器与刚性变化范围较大的外界工作环境接触时,具有较强的适应能力,较好地完成了机器人的力/位置控制。 相似文献
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基于遗传算法的双臂机器人模糊力/位混合控制 总被引:1,自引:0,他引:1
近年来,适用于空间站操作的冗余度双臂机器人系统技术研究得到了较多的重视.结合已有的
研究基础和研究条件,本文开展了面向空间舱内作业的冗余度双臂机器人协调控制应用研究.针对双臂机器
人协调操作过程中的受力问题,提出了一种基于遗传算法的双臂机器人模糊力/位混合控制策略.该方法把机
器人末端的力误差通过模糊控制转变为机器人位置控制器的修正值,在不改变机器人原有位置控制器的前提
下,实现力/位混合控制.利用遗传算法离线优化模糊控制规则,为了提高遗传算法的性能,总体交叉概率和
变异概率都采用了自适应控制策略.最后,以冗余度双臂机器人合力协调搬箱为例,进行了力跟踪的三维仿
真和实验,验证了所提出控制策略的有效性和可靠性. 相似文献
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机器人的力控制和顺应控制研究进展 总被引:5,自引:0,他引:5
机器人力控制和顺应控制是机器人学研究的一个重要领域,对于提高机器人的性能,增强机器人的适应性,扩大应用范围具有十分重要的意义.本文对近年来国内外关于机器人力控制和顺应控制方面的研究情况进行了综述,着重讨论环境约束下的机器人的力与位置混合控制,阻抗控制,刚度控制,阻尼控制,主动式顺应控制。被动式顺应控制(柔顺手腕),主动式柔顺手腕控制和机器人的自适应力控制.介绍了将人工神经元网络用于机器人力与位置控制的研究动态,最后指出了机器人力控制和顺应控制研究中存在的问题和研究方向. 相似文献
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双足机器人的双脚支撑期是实现其步行运动的重要过程,然而耦合的位置/力控制难以保证其稳定平滑运动.本文提出了一种基于降阶位置/力模型的机器人控制策略,整合了位置控制子空间模型和力控制子空间模型,通过模型降阶减小了控制器设计的复杂度,并采用神经网络自适应控制方法综合多控制目标,实现了双足机器人的平滑稳定控制并有效地抑制了系统外扰和参数不确定性的影响.最后,仿真算法验证了该控制方法和模型的有效性. 相似文献
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Hong-Rui Wang Li Yang Li-Xin Wei 《Soft Computing - A Fusion of Foundations, Methodologies and Applications》2007,11(4):311-315
The performance of a controller for robot force tracking is affected by the uncertainties in both the robot dynamic model and the environmental stiffness. This paper aims to improve the controller’s robustness by applying the neural network to compensate for the uncertainties of the robot model at the input trajectory level rather than at the joint torque level. A self-adaptive fuzzy controller is introduced for robotic manipulator position/force control. Simulation results based on a two-degrees of freedom robot show that highly robust position/force tracking can be achieved, despite the existence of large uncertainties in the robot model. 相似文献
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L. F. Baptista J. M. Sousa J. Sá da Costa 《Journal of Intelligent and Robotic Systems》2001,30(4):359-376
This paper proposes a force control strategy for robotic manipulators considering a non-rigid environment described by a nonlinear model. This approach uses a fuzzy predictive algorithm to generate, in an optimal way, the reference or virtual position to the classical impedance controller in order to apply a desired force profile on the environment. The main advantage of this control strategy is the possibility of including a nonlinear model of the environment in the controller design in a straightforward way, improving the global force control performance, especially in non-rigid environments. Moreover, in order to reduce the oscillations on the optimized reference position a fuzzy scaling machine is included on the force control strategy. The performance of the force control scheme is illustrated for a two degree-of-freedom PUMA 560 robot, which end-effector is forced to move along a flat surface located on the vertical plane. The simulation results obtained with the fuzzy control scheme reveal significant improvement in the force tracking performance, when compared to the impedance control with force tracking in non-rigid environments. 相似文献
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Neural Network Force Control for Industrial Robots 总被引:1,自引:0,他引:1
In this paper, we present a hierarchical force control framework consisting of a high level control system based on neural network and the existing motion control system of a manipulator in the low level. Inputs of the neural network are the contact force error and estimated stiffness of the contacted environment. The output of the neural network is the position command for the position controller of industrial robots. A MITSUBISHI MELFA RV-M1 industrial robot equipped with a BL Force/Torque sensor is utilized for implementing the hierarchical neural network force control system. Successful experiments for various contact motions are carried out. Additionally, the proposed neural network force controller together with the master/slave control method are used in dual-industrial robot systems. Successful experiments are carried out for the dual-robot system handling an object. 相似文献
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In this paper, a fuzzy force control framework is proposed for dual-industrial robot systems. The master/slave control method is used in dual-robot systems. Two MITSUBISHI MELFA RV-M1 industrial robots, one is equipped with an BL Force/Torque sensor and the other is not, are utilized for implementing the dual-arm system. In order to adapt various stiffness of the holding object, an adaptable fuzzy force control scheme has been proposed to improve the performance. The ability of the adaptable force control system is achieved by tuning the scaling factor of the fuzzy logic controller. Successful experiments are carried out for the dual-robot system handling an object. 相似文献
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机械臂的位置与力的混合控制方法 总被引:1,自引:0,他引:1
本文研究关于机械臂的位置与力的混合控制方法.为了实现混合控制,首先应用一对被
称为"任务规范投影算子"建立了机械臂混合控制的动态方程.在此基础上,提出了两种控制器
的设计方法,一种是计算力矩方法控制器,另一种是动态补偿变结构控制器.后者不但具有更
好的鲁棒性,并且可以分别调整运动与约束力的跟踪精度. 相似文献
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This article proposes an adaptive fuzzy control scheme for explicit force control of a robot manipulator in contact with an environment whose parameters are unknown and vary considerably. The scheme consists of three main components: a reference force model describing the desired behavior of the force control system, a fuzzy force controller that determines the adjustment to the position control loop, and a fuzzy learning and adaptation mechanism that modifies the fuzzy force controller according to the difference between the actual and desired force responses. The modification is performed by shifting and contracting/expanding the membership functions of the fuzzy sets associated with the consequent rules of the fuzzy force controller. It is demonstrated, through simulations of a two-link manipulator and a 6-DOF industrial robot, that the scheme is capable force tracking despite wide parameter variations, such as when the environment stiffness changes by several orders of magnitude. © 1997 John Wiley & Sons, Inc. 相似文献