物联网下并联机械手级联式控制仿真

Cascaded Control Simulation of Parallel Manipulators under the Internet of Things

针对当前机械手运动控制方法存在复杂度高、控制效果不理想的问题,提出物联网下并联机械手级联式控制方法。设定已知机械手,其连杆长度与关节角度均为已知值,以计算机械手正运动学解。根据机械手正运动学解,得到其运动学逆解。基于机械手运动学分析,引入级联式控制方式。根据级联方法具有的特性,提出将设计并联机械手非线性控制器转换为设计两个结构简单的线性控制器理念,即据级联方法将机械手轨迹跟踪控制分解为朝向角控制和坐标轴定位问题。利用角速度和线速度设计朝向角控制律下的线性控制器。设定两个非线性时变子体系,其中一个体系具备全局一致稳定性,将其输出当作另一个体系的扰动输入,第二个体系满足全局一致收敛性。当两个体系联结项满足机械手运动假设条件时,结合控制误差一阶导数方程,得到并联机械手级联定位控制律,实现机械手定位控制。实验结果表明,所提方法可实现机械手的高精度控制,且具有较低的复杂度,可行性强。

At present,the current manipulator motion control method leads to high complexity and unsatisfactory control.In this article,a cascaded control method for parallel manipulator under Internet of Things was proposed.Firstly,the known manipulator was set and its link length and joint angle were also known,which were used to calculate the positive kinematics of manipulator.According to the positive kinematics of manipulator,the inverse kinematics was obtained.Based on the kinematics analysis,a cascade control method was introduced.According to the characteristics of the cascaded method,it is proposed to convert the designed nonlinear the controller of parallel manipulator into the design of two simple linear controllers.That is to say,the trajectory tracking control of manipulator was decomposed into orientation angle control and coordinate axis positioning by the cascade method.After that,the linear controller oriented based on the angular control law was designed by angular velocity and linear velocity.Two nonlinear time-varying sub-systems were established,one of which has global uniform stability,and its output was treated as the perturbation input of another system.The second system satisfied the global uniform convergence.When the bonding terms of two systems satisfied the assumption of manipulator motion,the parallel manipulator positioning control law was obtained by combining with the first derivative equation of control error.Thus,we could achieve the manipulator positioning control.Simulation results prove that the proposed method can achieve high-precision control for the manipulator with low complexity and strong feasibility.