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A novel recursive formulation for dynamic modeling and trajectory tracking control of multi-rigid-link robotic manipulators mounted on a mobile platform

机译:用于移动平台上的多刚性连接机器人操纵器的动态建模和轨迹跟踪控制的新型递归制剂

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摘要

This article establishes an innovative and general approach for the dynamic modeling and trajectory tracking control of a serial robotic manipulator with n-rigid links connected by revolute joints and mounted on an autonomous wheeled mobile platform. To this end, first the Gibbs-Appell formulation is applied to derive the motion equations of the mentioned robotic system in closed form. In fact, by using this dynamic method, one can eliminate the disadvantage of dealing with the Lagrange Multipliers that arise from nonholonomic system constraints. Then, based on a predictive control approach, a general recursive formulation is used to analytically obtain the kinematic control laws. This multivariable kinematic controller determines the desired values of linear and angular velocities for the mobile base and manipulator arms by minimizing a point-wise quadratic cost function for the predicted tracking errors between the current position and the reference trajectory of the system. Again, by relying on predictive control, the dynamic model of the system in state space form and the desired velocities obtained from the kinematic controller are exploited to find proper input control torques for the robotic mechanism in the presence of model uncertainties. Finally, a computer simulation is performed to demonstrate that the proposed algorithm can dynamically model and simultaneously control the trajectories of the mobile base and the end-effector of such a complicated and high-degree-of-freedom robotic system.
机译:本文建立了具有旋转关节连接的n刚性环节的串行机器人操纵器的动态建模和轨迹跟踪控制的创新和一般方法,并安装在自主轮式移动平台上。为此,首先应用Gibbs-appell配方以在封闭形式推导所提述机器人系统的运动方程。实际上,通过使用这种动态方法,可以消除处理从非完整系统限制产生的拉格朗日乘法器的缺点。然后,基于预测性控制方法,一般递归制剂用于分析运动控制法。该多变量运动控制器通过最小化用于系统的当前位置和参考轨迹之间的预测跟踪误差来确定移动基座和操纵器臂的线性和角速度的所需值。同样,通过依靠预测控制,利用来自运动控制器获得的状态空间形式的动态模型以及从运动控制器获得的所需速度,以找到模型不确定性存在的机器人机制的适当输入控制扭矩。最后,执行计算机模拟以证明所提出的算法可以动态地模拟并同时控制移动基座的轨迹和这种复杂和高度自由度机器人系统的末端执行器。

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