迭代学习控制
趋同(经济学)
控制理论(社会学)
旋转副
计算机科学
线性化
非线性系统
正确性
机器人学
反馈线性化
分数阶微积分
系统动力学
控制工程
数学
控制(管理)
机器人
人工智能
算法
工程类
应用数学
物理
量子力学
经济
经济增长
作者
Mihailo Lazarević,Petar Mandić,Srđan Ostojić
标识
DOI:10.1177/0954406220965996
摘要
Recently, calculus of general order [Formula: see text] has attracted attention in scientific literature, where fractional operators are often used for control issues and the modeling of the dynamics of complex systems. In this work, some attention will be devoted to the problem of viscous friction in robotic joints. The calculus of general order and the calculus of variations are utilized for the modeling of viscous friction which is extended to the fractional derivative of the angular displacement. In addition, to solve the output tracking problem of a robotic manipulator with three DOFs with revolute joints in the presence of model uncertainties, robust advanced iterative learning control (AILC) is introduced. First, a feedback linearization procedure of a nonlinear robotic system is applied. Then, the proposed intelligent feedforward-feedback AILC algorithm is introduced. The convergence of the proposed AILC scheme is established in the time domain in detail. Finally, simulations on the given robotic arm system confirm the effectiveness of the robust AILC method.
科研通智能强力驱动
Strongly Powered by AbleSci AI