Neural Network Control of a Rehabilitation Robot by State and Output Feedback

被引：219

作者：

He, Wei ^{[1
,2
]}

Ge, Shuzhi Sam ^{[3
]}

Li, Yanan ^{[4
]}

Chew, Effie ^{[5
]}

Ng, Yee Sien ^{[6
]}

机构：

[1] Univ Elect Sci & Technol China, Ctr Robot, Chengdu 611731, Peoples R China

[2] Univ Elect Sci & Technol China, Sch Automat Engn, Chengdu 611731, Peoples R China

[3] Natl Univ Singapore, Dept Elect & Comp Engn, Singapore 117576, Singapore

[4] Agcy Sci Technol & Res, Inst Infocomm Res, Singapore 138632, Singapore

[5] Natl Univ Singapore Hosp, Div Neurol, Singapore 119074, Singapore

[6] Singapore Gen Hosp, Dept Rehabil Med, Singapore 169608, Singapore

来源：

JOURNAL OF INTELLIGENT & ROBOTIC SYSTEMS | 2015年 / 80卷 / 01期

基金：

中国国家自然科学基金;

关键词：

Adaptive neural network control; Full state feedback control; Lyapunov's direct method; Output feedback control; Rehabilitation robot; MULTIPLE MOBILE MANIPULATORS; ROBUST ADAPTIVE-CONTROL; MIMO NONLINEAR-SYSTEMS; TRACKING CONTROL; IMPEDANCE CONTROL; IDENTIFICATION;

D O I：

10.1007/s10846-014-0150-6

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, neural network control is presented for a rehabilitation robot with unknown system dynamics. To deal with the system uncertainties and improve the system robustness, adaptive neural networks are used to approximate the unknown model of the robot and adapt interactions between the robot and the patient. Both full state feedback control and output feedback control are considered in this paper. With the proposed control, uniform ultimate boundedness of the closed loop system is achieved in the context of Lyapunov's stability theory and its associated techniques. The state of the system is proven to converge to a small neighborhood of zero by appropriately choosing design parameters. Extensive simulations for a rehabilitation robot with constraints are carried out to illustrate the effectiveness of the proposed control.

引用

页码：15 / 31

页数：17

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