Adaptive Neural Network Control of Biped Robots

被引：148
作者：
Sun, Changyin [1 ]
He, Wei [2 ,3 ]
Ge, Weiliang [4 ,5 ]
Chang, Cheng [4 ,5 ]
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
[3] Univ Sci & Technol Beijing, Key Lab Adv Control Iron & Steel Proc, Beijing 100083, Peoples R China
[4] Univ Elect Sci & Technol China, Sch Automat Engn, Chengdu 611731, Peoples R China
[5] Univ Elect Sci & Technol China, Ctr Robot, Chengdu 611731, Peoples R China
来源：
IEEE TRANSACTIONS ON SYSTEMS MAN CYBERNETICS-SYSTEMS | 2017年 / 47卷 / 02期
基金：
中国国家自然科学基金;
关键词：
Adaptive control; balancing control; biped robots; neural networks; posture control; tracking control; DISCRETE-TIME-SYSTEMS; SLIDING-MODE CONTROL; CONSENSUS CONTROL; TRACKING CONTROL; FUZZY CONTROL; CRANE;
D O I：
10.1109/TSMC.2016.2557223
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, neural network control strategies based on radial basis functions are designed for biped robots, which includes balancing and posture control. To deal with system uncertainties, neural networks are used to approximate the unknown model of the robot. Both full state feedback control and output feedback control are considered in this paper. With the proposed control, the trajectories of the closed-loop system are semiglobally uniformly bounded which can be proved via Lyapunov stability theorem. Simulations are also carried out to illustrate the effectiveness of the proposed control.
引用
收藏
页码：315 / 326
页数：12
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