摘要
针对一种直线电机驱动的2-DOF并联机构,结合直线电机的动力学特性,采用Lagrange方法对其进行动力学建模。考虑该机构重复性动作及其不确定性和非线性特点,提出一种自适应神经网络迭代学习控制方法。在该控制算法的作用下,系统输出能较好地跟踪给定输入。严格证明及仿真结果验证了该算法的有效性。
The dynamic model of a kind of 2-DOF parallel mechanism driven by linear motor is established by Lagrange method combined with the dynamics characteristic of the linear motor. Adaptive neural network iterative learning control is proposed considering repetitive action, uncertainty and nonlinearity of the system. Using this control algorithm, the outputs of the system can track the desired trajectories. The strict proof and simulation results validate the validity of the controller.
出处
《计算机工程》
CAS
CSCD
北大核心
2009年第17期163-166,共4页
Computer Engineering
基金
河北省自然科学基金资助项目(F2009000500)
关键词
动力学建模
迭代学习控制
并联机构
不确定性
dynamic modeling
iterative learning control
parallel mechanism
uncertainty
