| Neuro-fuzzy adaptive control based on dynamic inversion for robotic manipulators | |
| Sun FC(孙富春); Sun ZQ(孙增圻); Li, L; Li, HX | |
| Department | 机器人学研究室 |
| Source Publication | FUZZY SETS AND SYSTEMS
 |
| ISSN | 0165-0114 |
| 2003 | |
| Volume | 134Issue:1Pages:117-133 |
| Indexed By | SCI ; EI ; CPCI（ISTP） |
| EI Accession number | 2003067352250 |
| WOS ID | WOS:000180682900008 |
| Contribution Rank | 1 |
| Keyword | Robotics Neuro-fuzzy Systems Dynamic Inversion Fuzzy Clustering Adaptive Control |
| Abstract | This paper presents a stable neuro-fuzzy (NF) adaptive control approach for the trajectory tracking of the robotic manipulator with poorly known dynamics. Firstly, the fuzzy dynamic model of the manipulator is established using the Takagi-Sugeno (T-S) fuzzy framework with both structure and parameters identified through input/output data from the robot control process. Secondly, based on the derived fuzzy dynamics of the robotic manipulator, the dynamic NF adaptive controller is developed to improve the system performance by adaptively modifying the fuzzy model parameters on-line. The dynamic NF system aims to approximate the whole robot dynamics rather than its nonlinear components as is done by static neural networks. The dynamic inversion introduced for the controller design is constructed by the dynamic NF system and will help the NF controller design because it does not require the assumption that the robot states should be within a compact set. It is generally known that the compact set cannot be specified before the control loop is closed. Thirdly, the system stability and the convergence of tracking errors are guaranteed by Lya-punov stability theory, and the learning algorithm for the dynamic NF system is obtained thereby. Finally, simulation studies are carried out to show the viability and effectiveness of the proposed control approach. |
| Language | 英语 |
| WOS Headings | Science & Technology ; Technology ; Physical Sciences |
| WOS Subject | Computer Science, Theory & Methods ; Mathematics, Applied ; Statistics & Probability |
| WOS Keyword | NONLINEAR-SYSTEMS ; NETWORKS ; DESIGN ; IDENTIFICATION ; STABILITY ; MODELS |
| WOS Research Area | Computer Science ; Mathematics |
| Citation statistics | |
| Document Type | 期刊论文 |
| Identifier | http://ir.sia.cn/handle/173321/7382 |
| Collection | 机器人学研究室 |
| Corresponding Author | Sun FC(孙富春) |
| Affiliation | 1.Dept. of Comp. Sci. and Technology, State Key Lab Intell. Techno./Syst., Beijing 100084, China 2.Robotics Laboratory, Shenyang Institute of Automation, Chinese Academy of Sciences, Shenyang 110015, China 3.Institute of Software, Tsinghua University, Chinese Academy of Science, Beijing 100084, China 4.Dept. of Mfg. Eng./Eng. Management, City University of Hong Kong, Hong Kong, Hong Kong |
| Recommended Citation GB/T 7714 | Sun FC,Sun ZQ,Li, L,et al. Neuro-fuzzy adaptive control based on dynamic inversion for robotic manipulators[J]. FUZZY SETS AND SYSTEMS,2003,134(1):117-133. |
| APA | Sun FC,Sun ZQ,Li, L,&Li, HX.(2003).Neuro-fuzzy adaptive control based on dynamic inversion for robotic manipulators.FUZZY SETS AND SYSTEMS,134(1),117-133. |
| MLA | Sun FC,et al."Neuro-fuzzy adaptive control based on dynamic inversion for robotic manipulators".FUZZY SETS AND SYSTEMS 134.1(2003):117-133. |
| Files in This Item: | Download All | |||||
| File Name/Size | DocType | Version | Access | License | ||
| YWQK000209.pdf（311KB） | 期刊论文 | 出版稿 | 开放获取 | ODC PDDL | View Download | |
Items in the repository are protected by copyright, with all rights reserved, unless otherwise indicated.
Edit Comment