Fuzzy Neural Network Control of a Flexible Robotic Manipulator Using Assumed Mode Method

被引：127

作者：

Sun, Changyin ^{[1
]}

Gao, Hejia ^{[2
]}

He, Wei ^{[2
]}

Yu, Yao ^{[2
]}

机构：

[1] Southeast Univ, Sch Automat, Nanjing 210096, Jiangsu, Peoples R China

[2] Univ Sci & Technol Beijing, Sch Automat & Elect Engn, Beijing 100083, Peoples R China

来源：

IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS | 2018年 / 29卷 / 11期

基金：

中国国家自然科学基金;

关键词：

Adaptive control; assumed mode method (AMM); dynamic modeling; flexible robotic manipulator; neural networks (NNs); vibration control; VIBRATION CONTROL; BOUNDARY CONTROL; DYNAMIC-SYSTEMS; SLIDING-MODE; TRACKING; DESIGN;

D O I：

10.1109/TNNLS.2017.2743103

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

In this paper, in order to analyze the single-link flexible structure, the assumed mode method is employed to develop the dynamic model. Based on the discrete dynamic model, fuzzy neural network (NN) control is investigated to track the desired trajectory accurately and to suppress the flexible vibration maximally. To ensure the stability rigorously as the goal, the system is proved to be uniform ultimate boundedness by Lyapunov's stability method. Eventually, simulations verify that the proposed control strategy is effective, and the control performance is compared with the proportion derivative control. The experiments are implemented on the Quanser platform to further demonstrate the feasibility of the proposed fuzzy NN control.

引用

页码：5214 / 5227

页数：14

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