Neural Network Control of a Two-Link Flexible Robotic Manipulator Using Assumed Mode Method

被引：208

作者：

Gao, Hejia ^{[1
,2
]}

He, Wei ^{[1
,2
]}

Zhou, Chen ^{[1
,2
]}

Sun, Changyin ^{[3
]}

机构：

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

[2] Univ Sci & Technol Beijing, Minist Educ, Key Lab Knowledge Automat Ind Proc, Beijing 100083, Peoples R China

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

来源：

IEEE TRANSACTIONS ON INDUSTRIAL INFORMATICS | 2019年 / 15卷 / 02期

基金：

中国国家自然科学基金;

关键词：

Assumed mode method (AMM); dynamic modeling; flexible robotic manipulator; flexible structure; neural networks (NN); vibration control; two-link; NONLINEAR-SYSTEMS; VIBRATION CONTROL; BOUNDARY CONTROL; TRACKING; EQUATION;

D O I：

10.1109/TII.2018.2818120

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

In this paper, the n-dimensional discretized model of the two-link flexible manipulator is developed by the assumed mode method (AMM). Subsequently, based on the discretized dynamic model, both full-state feedback control and output feedback control are investigated to achieve the trajectory tracking and vibration suppression. In order to guarantee the stability strictly, uniform ultimate boundedness (UUB) of the closed-loop system is realized by the Lyapunov's stability. Furthermore, through appropriately choosing control parameters, the states of the system will converge to zero within a small neighborhood. Eventually, extensive simulations and experiments on the Quanser platform for a two-link robotic manipulator are carried out to demonstrate the feasibility of the proposed neural network controller.

引用

页码：755 / 765

页数：11

共 38 条

[1] ROBUST OUTPUT TRACKING FOR NONLINEAR-SYSTEMS [J].

BEHTASH, S .

INTERNATIONAL JOURNAL OF CONTROL, 1990, 51 (06) :1381-1407

[2] Modeling of Flexible Robots With Varying Cross Section and Large Link Deformations [J].

Celentano, Laura .

JOURNAL OF DYNAMIC SYSTEMS MEASUREMENT AND CONTROL-TRANSACTIONS OF THE ASME, 2016, 138 (02)

[3] A computationally efficient method for modeling flexible robots based on the assumed modes method [J].

Celentano, Laura ;

Coppola, Alessandro .

APPLIED MATHEMATICS AND COMPUTATION, 2011, 218 (08) :4483-4493

[4] Adaptive fuzzy controller of the overhead cranes with nonlinear disturbance [J].

Chang, Cheng-Yuan .

IEEE TRANSACTIONS ON INDUSTRIAL INFORMATICS, 2007, 3 (02) :164-172

[5] Dynamic modeling of multi-link flexible robotic manipulators [J].

Chen, W .

COMPUTERS & STRUCTURES, 2001, 79 (02) :183-195

[6] A recurrent neural-network-based real-time learning control strategy applying to nonlinear systems with unknown dynamics [J].

Chow, TWS ;

Fang, Y .

IEEE TRANSACTIONS ON INDUSTRIAL ELECTRONICS, 1998, 45 (01) :151-161

[7] Platoon Formation Control With Prescribed Performance Guarantees for USVs [J].

Dai, Shi-Lu ;

He, Shude ;

Lin, Hai ;

Wang, Cong .

IEEE TRANSACTIONS ON INDUSTRIAL ELECTRONICS, 2018, 65 (05) :4237-4246

[8] Neural Learning Control of Marine Surface Vessels With Guaranteed Transient Tracking Performance [J].

Dai, Shi-Lu ;

Wang, Min ;

Wang, Cong .

IEEE TRANSACTIONS ON INDUSTRIAL ELECTRONICS, 2016, 63 (03) :1717-1727

[9] Dynamic Learning From Adaptive Neural Network Control of a Class of Nonaffine Nonlinear Systems [J].

Dai, Shi-Lu ;

Wang, Cong ;

Wang, Min .

IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS, 2014, 25 (01) :111-123

[10] CLOSED-FORM DYNAMIC-MODEL OF PLANAR MULTILINK LIGHTWEIGHT ROBOTS [J].

DELUCA, A ;

SICILIANO, B .

IEEE TRANSACTIONS ON SYSTEMS MAN AND CYBERNETICS, 1991, 21 (04) :826-839

← 1 2 3 4 →