具有量化输入机械臂系统的预设性能自适应神经网络控制

doi:10.16180/j.cnki.issn1007-7820.2024.12.005

电子科技 ›› 2024, Vol. 37 ›› Issue (12): 32-36.doi: 10.16180/j.cnki.issn1007-7820.2024.12.005

具有量化输入机械臂系统的预设性能自适应神经网络控制

楚东港, 刘烨

上海工程技术大学电子电气工程学院,上海 201620

收稿日期:2023-03-16 出版日期:2024-12-15 发布日期:2024-12-16
作者简介:楚东港(1997-),男,硕士研究生。研究方向:自适应控制。
刘烨(1984-),女,博士,副教授。研究方向:自适应控制和非线性系统。
基金资助:
国家自然科学基金(61703269)

Predefined Performance Adaptive Neural Network Control of Manipulator System with Quantized Input

CHU Donggang, LIU Ye

School of Electronic and Electrical Engineering,Shanghai University of Engineering Science, Shanghai 201620,China

Received:2023-03-16 Online:2024-12-15 Published:2024-12-16
Supported by:
National Natural Science Foundation of China(61703269)

摘要/Abstract

摘要：

针对具有量化输入的单连杆机械臂系统,文中提出了基于Funnel控制的预设性能自适应神经网络控制方法。不同于传统Funnel控制方案,该方法通过构建新型性能函数可保证系统在预定时间达到预设的性能指标,并且使用径向基神经网络和动态面控制技术解决了系统中的未知非线性项与传统反步控制方法中的微分爆炸问题。理论分析证明,所提控制方案不仅消除了量化输入引起的负面影响,而且保证了系统的稳定性。通过调节MTLAB仿真实验中的设计参数,实现了跟踪误差的预定时间收敛,验证了所提控制方法的有效性。

关键词: 自适应控制, 动态面控制, Funnel控制, 径向基神经网络, 预设性能, 输入量化, 机械臂系统, 外部扰动

Abstract:

In view of the single-link manipulator system with quantized input, a predefined performance adaptive neural network control method based on Funnel control is proposed in this study. Different from the traditional Funnel control scheme, this method can ensure that the system reaches the predefined performance index within the predetermined time by constructing a new performance function, and the neural network and dynamic surface control technology are used to solve the unknown nonlinear items in the system and the differential explosion problem in the traditional backstepping control method. Theoretical analysis shows that the proposed control scheme not only eliminates the negative effects caused by quantized inputs, but also ensures the stability of the system. By adjusting the design parameters in the MATLAB simulation experiment, the predetermined time convergence of the tracking error is realized, which verifies the effectiveness of the proposed control method.

Key words: adaptive control, dynamic surface control, Funnel control, radial basis function neural network, prescribed performance, input quantization, manipulator system, external disturbance

中图分类号:

TP273

楚东港, 刘烨. 具有量化输入机械臂系统的预设性能自适应神经网络控制[J]. 电子科技, 2024, 37(12): 32-36.

CHU Donggang, LIU Ye. Predefined Performance Adaptive Neural Network Control of Manipulator System with Quantized Input[J]. Electronic Science and Technology, 2024, 37(12): 32-36.

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参数	含义	取值	单位
M	连杆质量	1.00	kg
L	连杆长度	1.00	m
g	重力加速度	9.80	m·s^-2
N	电机转动惯量	0.01	m·s^-2
G	自然阻尼系数	1.00	N·m·rad^-1
B	弹性系数	1.00	-
ℓ	摩擦系数	0.01	-

具有量化输入机械臂系统的预设性能自适应神经网络控制

Predefined Performance Adaptive Neural Network Control of Manipulator System with Quantized Input

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