共查询到19条相似文献,搜索用时 968 毫秒
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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:1,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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提出一种由神经网络训练模糊控制规则的自适应模糊控制器,并应用附加力外环的机器人力/位置控制。在不改变一般工业机器人原有位置控制的前提下,实现力/位置自适应模糊控制。实验结果表明,该方法可使机器人控制系统对工作环境接触刚度的自适应能力得到显著改善。 相似文献
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针对大射电望远镜馈源舱跟踪定位问题,提出一种自适应滑模控制方法.从线性化模型出发.将模型偏差、风载荷视为系统外部扰动,通过引入参数自适应机制,在线估计外部扰动并加以补偿.采用Lyapunov稳定性理论,推导了舱索系统的多输入多输出自适应滑模控制律.在此基础上,针对大射电望远镜50m缩尺模型,采用离散悬索模型和自适应滑模控制方法对舱索控制系统进行了仿真,并与传统的PID控制方法进行对比.结果表明,采用自适应滑模控制使跟踪误差减小到约32%,并提高了抗风扰能力. 相似文献
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CTU料箱机器人在多层拣货期间会出现装载不稳定现象,为解决这一问题,该文提出CTU机器人装载轨迹自适应模糊滑模控制方法。对CTU料箱机器人实施动力学分析,依据分析结果规划CTU机器人装载轨迹路径,使机器人根据规划的最优路径实现自动化取货;为保持机器人在拣货期间的稳定性,利用构建的自适应模糊滑模控制模型消除CTU机器人在外界干扰下所产生的输入抖振现象,并结合设计的自适应控制律,完成CTU机器人装载轨迹平衡控制,从而实现CTU机器人装载轨迹自适应模糊滑模控制。实验结果表明,通过对该方法开展平衡能力及抗扰动性测试,验证了该方法的可行性。 相似文献
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提出一种改进学习算法的CAMC网络结构,并应用于非线性系统控制。该算法可保证网络的学习率随着系统工作点的变化而自适应变化,加快了网络的收敛速度,提高了系统的自适应能力。文中分析了CAMC网络用于自适应逆控制过程中,网络学习率对网络收敛特性的影响,论证了自适应学习率在网络学习中的作用,并给出了学习率自适应学习的具体训练方法。最终将该方法应用于三阶机械手模型的逆运动控制,给出了基于普通CMAC的逆运动控制的控制曲线和基于改进学习算法后的CMAC的逆运动控制的控制曲线,并给出了分析和对比,论证了改进的学习算法的优越性。 相似文献
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As a key technology of robot grinding, force control has great influence on grinding effects. Based on the traditional impedance control, a position-based force tracking adaptive impedance control strategy is proposed to improve the grinding quality of aeroengine complex curved parts, which considers the stiffness damping environmental interaction model, modifies the reference trajectory by a Lyapunov-based approach to realize the adaptive grinding process. In addition, forgotten Kalman filter based on six-dimensional force sensor is used to denoise the force information and a three-step gravity compensation process including static base value calculation, dynamic zero update and contact force real-time calculation is proposed to obtain the accurate contact force between tool and workpiece in this method. Then, to verify the effectiveness of the proposed method, a simulation experiment which including five different working conditions is conducted in MATLAB, and the experiment studying the deviation between the reference trajectory and the actual position is carried out on the robot grinding system. The results indicate that the position-based force tracking adaptive impedance control strategy can quickly respond to the changes of environmental position, reduce the fluctuation range of contact force in time by modifying the reference trajectory, compensate for the defect of the steady-state error of the traditional impedance control strategy and improve the surface consistency of machined parts. 相似文献
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飞行机械臂系统的接触力控制 总被引:1,自引:0,他引:1
针对飞行机械臂系统的接触力控制问题,本文首先从理论上证明了闭环无人机系统具有与弹簧-质量-阻尼系统一致的动态特性.基于飞行机械臂接触状态下力的分析,得到了无人机水平前向接触力与系统重力和俯仰角之间的动态关系,进而分析出接触力控制可以不使用力传感器来实现.根据阻抗控制思想,提出了飞行机械臂系统接触力控制方法,即通过同时控制位置偏差和对应姿态角度来实现接触力的控制.给出了单自由度飞行机械臂系统动力学模型,对应分析出系统的稳定性.开发了基于四旋翼飞行器的单自由度飞行机械臂系统,并进行了实际的飞行实验,验证了所提出接触力控制方法的有效性,同时也证实了所开发系统的可靠性. 相似文献
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针对飞行机械臂系统移动接触作业问题,使用了一个力/位置混合控制框架,用以控制飞行器系统持续可靠地接触外部环境同时保持一定大小的接触力,并实现在接触过程中的期望轨迹跟踪.首先将作业空间分成2个子空间--约束空间和自由空间,并分别进行力控制和位置控制.对于力控制问题,证明闭环无人机系统是一个类弹簧-质量-阻尼系统,然后在约束子空间中设计逆动力学控制器来实现接触力控制.自由飞行空间中的运动控制依靠轨迹规划和位置控制器来实现.最后,开发了基于六旋翼飞行机器人的单自由度飞行机械臂系统,在飞行状态下进行接触墙面并跟踪倾斜直线轨迹的实验.结果显示本文所使用方法能够保证在平稳移动的同时控制期望的接触力. 相似文献
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为了解决机器人在特定接触环境操作时对可以产生任意作用力柔性的高要求和机器人在自由空间操作时对位置伺服刚度及机械结构刚度的高要求之间的矛盾.对机器人力控制问题进行了研究,利用机械动力学仿真软件ADAMS/VIEW建立关节机器人的虚拟样机模型,通过其输入输出接口实现与MATLAB的通信,基于SIMULINK建立关节机器人力控制系统模型,将联合仿真概念引入到机器人力控制领域,最后进行仿真试验,对控制算法进行仿真验证,以提高控制精度和控制质量,通过对仿真结果的分析和处理证明此方法的合理性和有效性,为机器人力控制提供了一套有效的分析方法. 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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Effective haptic performance in teleoperation control systems can be achieved by solving two major problems: the time‐delay in communication channels and the transparency of force control. The time‐delay in communication channels causes poor performance and even instability in a system. The transparency of force feedback is important for an operator to improve the performance of a given task. This article suggests a possible solution for these two problems through the implementation of a teleoperation control system between the master haptic device and the slave mobile robot. Regulation of the contact force in the slave mobile robot is achieved by introducing a position‐based impedance force control scheme in the slave robot. The time‐delay problem is addressed by forming a Smith predictor configuration in the teleoperation control environment. The configuration of the Smith predictor structure takes the time‐delay term out of the characteristic equation in order to make the system stable when the system model is given a priori. Since the Smith predictor is formulated from exact linear modeling, a neural network is employed to identify and model the slave robot system as a nonlinear model estimator. Simulation studies of several control schemes are performed. Experimental studies are conducted to verify the performance of the proposed control scheme by regulating the contact force of a mobile robot through the master haptic device. 相似文献
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Accurate robotic belt grinding of workpieces with complex geometries using relative calibration techniques 总被引:2,自引:0,他引:2
Robotic belt grinding operations are performed by mounting a workpiece to the end effector and commanding it to move along a trajectory while maintaining contact with the belt grinding wheel. A constant contact force throughout the grinding process is necessary to provide a smooth finish on the workpiece, but it is difficult to maintain this force due to a multitude of installation, manipulation, and calibration errors. The following describes a novel methodology for robotic belt grinding, which primarily focuses on system calibration and force control to improve grinding performance. The overall theory is described and experimental results of turbine blade grinding for each step of the methodology are shown. 相似文献