考虑未知负载的机械臂任务空间模糊跟踪控制  

Adaptive fuzzy control for robot manipulators with uncertain load in task-space

作　　者：徐恩华[1] 徐燕[2] 黄宇飞[2] 

机构地区：[1]广州民航职业技术学院飞机维修工程学院,广东广州510403 [2]广州民航职业技术学院数学教学部,广东广州510403

出　　处：《中山大学学报（自然科学版）》2016年第2期7-13,共7页Acta Scientiarum Naturalium Universitatis Sunyatseni

基　　金：国家自然科学基金资助项目(11501139)

摘　　要：针对机械臂任务空间控制中动力学参数及负载均未知,导致末端轨迹跟踪难以实现的问题,提出了一种自适应模糊控制器(AFC)设计方法。采用一个滤波器滤除由末端位置微分获得的速度信号中的噪声;根据关节速度与Jacobian矩阵估计末端速度,并将估计误差引入控制器设计;通过另一个滤波器对误差函数进行处理。控制律由两部分组成,第一部分是一个模糊逻辑系统的输出,用来逼近机械臂动力学模型中包含摩擦等在内的非线性环节;第二部分是一个鲁棒项,用来减小系统外部扰动及模糊逼近误差带来的影响。通过Lyapunov方法设计控制器并证明了闭环系统的稳定性。Matlab环境下的对比仿真表明,本文所提方法下,机械臂末端跟踪轨迹平滑,且保持较高的跟踪精度。An adaptive fuzzy controller（ AFC） is proposed by considering the uncertain payload as well as robot dynamics in task space. To eliminate the noise from the velocity obtained by the differential of position,the velocity is filtered by a low-pass filter,while,the task-space velocity is estimated by the Jacobian matrix. The estimation error is considered in the controller design. And another low-pass filter is used to build the error function. The control law is composed of two parts. The first part is a fuzzy logic system approximating the nonlinear term of the robot dynamics,including friction; and the second part is a robust term to reduce the approximate error of the fuzzy logic system as well as the uncertain external disturbance. Using Lyapunov theory,the controller is given and the stability of the closed-loop system is proved. Comparing simulink results by using matlab show that,the tracking tajectory of the end-effector under the proposed AFC controller has good accuracy and smoothness.

关 键 词：机械臂 任务空间 模糊逻辑系统 自适应控制 未知参数 

分 类 号：TP241[自动化与计算机技术—检测技术与自动化装置]