An Observer-Based Neural Adaptive <inline-formula><tex-math notation='LaTeX'>$PID^2$</tex-math></inline-formula> Controller for Robot Manipulators Including Motor Dynamics With a Prescribed Performance

Shojaei Khoshnam; Kazemy Ali; Chatraei Abbas

首页> 外文期刊>Mechatronics, IEEE/ASME Transactions on >An Observer-Based Neural Adaptive

$PID^2$

Controller for Robot Manipulators Including Motor Dynamics With a Prescribed Performance

【24h】

An Observer-Based Neural Adaptive $PID^2$ Controller for Robot Manipulators Including Motor Dynamics With a Prescribed Performance

机译：基于观察者的神经自适应<内联公式> $ PID ^ 2 $ 控制器，用于机器人操纵器，包括具有规定性能的电机动态

获取原文

获取原文并翻译 | 示例

掌桥外文数据库（机构版） >>

开具论文收录证明 >>

文献代查 >>

页面导航

摘要
著录项
相似文献
相关主题

摘要

This article proposes a novel prescribed performance-based neural adaptive control scheme for robot manipulators including motor dynamics under model uncertainties without velocity, acceleration, and input current measurements. The prescribed performance function approach is used to transform a constrained tracking problem of the robot model including motor dynamics into an unconstrained third-order error model in Euler-Lagrange form which inherits all properties of the robot dynamics. Then, a projection-type neural adaptive PID2 controller (a PID controller with the second-order derivative) in conjunction with a velocity-acceleration observer is proposed. Lyapunov's direct method is used to prove that the tracking and state observation errors are semiglobally uniformly ultimately bounded and converge to a small ball around the origin with a prescribed overshoot/undershoot, convergence rate, and final tracking accuracy. Finally, simulation, experimental results on a SCARA robot and comparative studies verify that the proposed controller is effective for the joint position trajectory tracking of robot manipulators in the industrial automation with minimum measurement and hardware requirements.

机译：本文提出了一种用于机器人操纵器的新规定的基于性能的神经自适应控制方案，包括在没有速度，加速度和输入电流测量的模型不确定性下的电动机动力学。规定的性能函数方法用于将机器人模型的约束跟踪问题转换为euler-lagrange形式中的电机动力学中的无约束三阶错误模型，其继承机器人动态的所有属性。然后，提出了一种与速度加速观察者结合速度 - 加速观察者的投影型神经自适应PID2控制器（具有二阶导数的PID控制器。 Lyapunov的直接方法用于证明跟踪和状态观察误差是半球性均匀的最终界定的，并收敛到围绕原点的小球，具有规定的过冲/下冲，收敛速度和最终跟踪精度。最后，仿真，对斯卡拉机器人和比较研究的实验结果验证了所提出的控制器对于工业自动化中的机器人操纵器的联合位置轨迹跟踪，具有最小的测量和硬件要求。

著录项

来源
《Mechatronics, IEEE/ASME Transactions on》 |2021年第3期|1689-1699|共11页
作者
Shojaei Khoshnam; Kazemy Ali; Chatraei Abbas;
展开▼
作者单位

Islamic Azad Univ Dept Elect Engn Najafabad Branch Najafabad Iran|Islamic Azad Univ Digital Proc & Machine Vis Res Ctr Najafabad Branch Najafabad Iran;

Tafresh Univ Dept Elect Engn Tafresh 3951879611 Iran;

Islamic Azad Univ Dept Elect Engn Najafabad Branch Najafabad Iran|Islamic Azad Univ Digital Proc & Machine Vis Res Ctr Najafabad Branch Najafabad Iran;

展开▼
收录信息
原文格式 PDF
正文语种 eng
中图分类
关键词
Neural adaptive control; observer-based control; prescribed performance; PID2 control; robot manipulator;

机译：神经自适应控制;基于观察者的控制;规定的性能;PID2控制;机器人操纵器;

相似文献

外文文献

1. Neural-network-based two-loop control of robotic manipulators including actuator dynamics in task space [J] . Liangyong WANG, Tianyou CHAI, Zheng FANG 控制理论与应用：英文版 . 2009,第002期
2. Neural-network-based two-loop control of robotic manipulators including actuator dynamics in task space [J] . Liangyong WANG, Tianyou CHAI, Zheng FANG 控制理论与应用（英文版） . 2009,第002期
3. Closed-Loop d${bm i}/$d ${bm t}$ and d ${bm v}/$d${bm t}$ IGBT Gate Driver [J] . Lobsiger Y., Kolar J.W. Power Electronics, IEEE Transactions on . 2015,第6期

机译：闭环d $ {bm i} / $ d $ {bm t} $ 和d $ {bm v} / $ d $ {bm t} $ IGBT栅极驱动器
4. Reliability and Reliability Importance of Weighted-$r$-Within-Consecutive-$k$-out-of-$n: F$System [J] . Kirtee K. Kamalja, Kalpesh P. Amrutkar IEEE Transactions on Reliability . 2018,第3期

机译：加权- $ r $ -连续内- $ k $ -out-of- $ n：F $ 系统
5. On the$l_2$-$l_infty$and$H_infty$Perform [J] . Choon Ki Ahn, Shunyi Zhao, Yuriy S. Shmaliy, Circuits and Systems II: Express Briefs, IEEE Transactions on . 2018,第11期

机译：在 $ l_2 $ - $ l _ infty $ 和 $ H _ infty $ 执行
6. Adaptive neural network tracking control of robot manipulators including motor dynamics: Dynamic surface backstepping methodology [C] . Xiwen Guo, Qunjing Wang, Cungang Hu, International Conference on Industrial Mechatronics and Automation . 2010

机译：机器人操纵器的自适应神经网络跟踪控制，包括电机动力学：动态表面反向梗方法
7. Direct neural-adaptive control of robotic manipulators using a forward dynamics approach. [D] . Beirami, Arash. 2006

机译：使用前向动力学方法对机器人机械手进行直接的神经自适应控制。
8. A Highly Birefringent and Nonlinear AsSe $_2$ –As $_2$ S $_5$ Photonic Crystal Fiber With Two Zero-Dispersion Wavelengths [O] . Tianyu Yang, Can Ding, Y. Jay Guo 2019

机译：一个高度双折射和非线性ASSE $ _ 2 $ -as <内联公式> $ _ 2 $ s $ _ 5 $ photonic具有两个零色散波长的晶体纤维
9. Dynamic modeling, property investigation, and adaptive controller design of serial robotic manipulators modeled with structural compliance [R] . Tesar, Delbert, Tosunoglu, Sabri, Lin, Shyng-Her 1990

机译：动态建模，属性调查和串行机器人操纵器的自适应控制器设计与结构顺应性建模

An Observer-Based Neural Adaptive $PID^2$ Controller for Robot Manipulators Including Motor Dynamics With a Prescribed Performance

摘要

著录项

相似文献

相关主题

期刊订阅