[1]周波,戴先中.基于SR-UKF的移动机器人主动故障检测和容错控制[J].东南大学学报(自然科学版),2011,41(5):1002-1007.[doi:10.3969/j.issn.1001-0505.2011.05.021]
 Zhou Bo,Dai Xianzhong.SR-UKF based active fault detection and tolerant control of mobile robots[J].Journal of Southeast University (Natural Science Edition),2011,41(5):1002-1007.[doi:10.3969/j.issn.1001-0505.2011.05.021]
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基于SR-UKF的移动机器人主动故障检测和容错控制()
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《东南大学学报(自然科学版)》[ISSN:1001-0505/CN:32-1178/N]

卷:
41
期数:
2011年第5期
页码:
1002-1007
栏目:
自动化
出版日期:
2011-09-20

文章信息/Info

Title:
SR-UKF based active fault detection and tolerant control of mobile robots
作者:
周波戴先中
(东南大学自动化学院,南京 210096)
Author(s):
Zhou BoDai Xianzhong
(School of Automation, Southeast University, Nanjing 210096, China)
关键词:
移动机器人SR-UKF故障检测容错控制
Keywords:
mobile robot square-rooted unscented Kalman filter (SR-UKF) fault detection tolerant control
分类号:
TP13;TP24
DOI:
10.3969/j.issn.1001-0505.2011.05.021
摘要:
提出了一种基于SR-UKF的主动状态建模方法用于移动机器人的在线故障检测和容错跟踪控制.通过对履带式机器人常见滑动故障的运动学分析,建立了带未知滑动故障参数的机器人运动学模型,并采用SR-UKF非线性滤波方法来联合估计机器人的位姿和滑动参数,在对机器人进行实时定位的同时实现了对快速变化(或突变)的滑动故障的在线跟踪和检测.在此基础上,将估计得到的自适应参数模型与基于Lyapunov分析的反馈控制律设计方法结合,获得了一致渐近稳定的轨迹跟踪控制结果,实现了针对在线故障自适应模型的容错控制重构.针对典型的阶跃式滑动故障参数变化的轨迹跟踪仿真实验表明了该方法的有效性.
Abstract:
A square-rooted unscented Kalman filter (SR-UKF) based active state model is proposed for online fault detection and tolerant tracking control of mobile robots. The common slipping fault of a tracked vehicle is considered and the corresponding kinematic model with unknown slipping parameters is created. The slipping parameters as well as the pose of the robot are estimated simultaneously by the joint estimation framework to realize the real-time localization of robots and online identification and detection of the fast changing (or even abrupt changing) slipping fault. The obtained adaptive fault model is then incorporated to the tolerant control configuration in which a Lyapunov based feedback law is designed to achieve uniformly asymptotic stable trajectory tracking control. Simulation experiments for trajectory tracking with typical step changing slipping faults show the efficiency of the proposed method.

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备注/Memo

备注/Memo:
作者简介:周波(1981—),男,博士,讲师,zhoubo@seu.edu.cn.
基金项目:国家自然科学基金资助项目(61005092)、教育部博士点新教师基金资助项目(20100092120026).
引文格式: 周波,戴先中.基于SR-UKF的移动机器人主动故障检测和容错控制[J].东南大学学报:自然科学版,2011,41(5):1002-1007.[doi:10.3969/j.issn.1001-0505.2011.05.021]
更新日期/Last Update: 2011-09-20