Trajectory Tracking Control of Omnidirectional Wheeled Mobile Manipulators: Robust Neural Network-Based Sliding Mode Approach
文献类型：期刊论文
| 作者 | Xu, Dong1,2; Zhao, Dongbin1 ; Yi, Jianqiang1; Tan, Xiangmin1
|
| 刊名 | IEEE TRANSACTIONS ON SYSTEMS MAN AND CYBERNETICS PART B-CYBERNETICS
 |
| 出版日期 | 2009-06-01 |
| 卷号 | 39期号:3页码:788-799 |
| 关键词 | Omnidirectional mobile manipulators robust neural network (NN) sliding mode control (SMC) trajectory tracking control uncertainties |
| 英文摘要 | This paper addresses the robust trajectory tracking problem for a redundantly actuated omnidirectional mobile manipulator in the presence of uncertainties and disturbances. The development of control algorithms is based on sliding mode control (SMC) technique. First, a dynamic model is derived based on the practical omnidirectional mobile manipulator system. Then, a SMC scheme, based on the fixed large upper boundedness of the system dynamics (FLUBSMC), is designed to ensure trajectory tracking of the closed-loop system. However, the FLUBSNIC scheme has inherent deficiency, which needs computing the upper boundedness of the system dynamics, and may cause high noise amplification and high control cost, particularly for the complex dynamics of the omnidirectional mobile manipulator system. Therefore, a robust neural network (NN)-based sliding mode controller (NNSMC), which uses an NN to identify the unstructured system dynamics directly, is further proposed to overcome the disadvantages of FLUBSMC and reduce the online computing burden of conventional NN adaptive controllers. Using learning ability of NN, NNSMC can coordinately control the omnidirectional mobile platform and the mounted manipulator with different dynamics effectively. The stability of the closed-loop system, the convergence of the NN weight-updating process, and the boundedness of the NN weight estimation errors are all strictly guaranteed. Then, in order to accelerate the NN learning efficiency, a partitioned NN structure is applied. Finally, simulation examples are given to demonstrate the proposed NNSMC approach can guarantee the whole system's convergence to the desired manifold with prescribed performance. |
| WOS标题词 | Science & Technology ; Technology |
| 类目[WOS] | Automation & Control Systems ; Computer Science, Artificial Intelligence ; Computer Science, Cybernetics |
| 研究领域[WOS] | Automation & Control Systems ; Computer Science |
| 关键词[WOS] | SYSTEMS ; ROBOTS ; MOTION |
| 收录类别 | SCI |
| 语种 | 英语 |
| WOS记录号 | WOS:000266069600016 |
| 源URL | [http://ir.ia.ac.cn/handle/173211/3590]  |
| 专题 | 自动化研究所_复杂系统管理与控制国家重点实验室_先进控制与自动化团队 |
| 作者单位 | 1.Chinese Acad Sci, Inst Automat, Key Lab Complex Syst & Intelligence Sci, Beijing 100190, Peoples R China 2.Beijing Sevenstar Elect Co Ltd, IC Proc Equipment R&D Ctr, Beijing 100016, Peoples R China |
| 推荐引用方式 GB/T 7714 | Xu, Dong,Zhao, Dongbin,Yi, Jianqiang,et al. Trajectory Tracking Control of Omnidirectional Wheeled Mobile Manipulators: Robust Neural Network-Based Sliding Mode Approach[J]. IEEE TRANSACTIONS ON SYSTEMS MAN AND CYBERNETICS PART B-CYBERNETICS,2009,39(3):788-799. |
| APA | Xu, Dong,Zhao, Dongbin,Yi, Jianqiang,&Tan, Xiangmin.(2009).Trajectory Tracking Control of Omnidirectional Wheeled Mobile Manipulators: Robust Neural Network-Based Sliding Mode Approach.IEEE TRANSACTIONS ON SYSTEMS MAN AND CYBERNETICS PART B-CYBERNETICS,39(3),788-799. |
| MLA | Xu, Dong,et al."Trajectory Tracking Control of Omnidirectional Wheeled Mobile Manipulators: Robust Neural Network-Based Sliding Mode Approach".IEEE TRANSACTIONS ON SYSTEMS MAN AND CYBERNETICS PART B-CYBERNETICS 39.3(2009):788-799. |
入库方式： OAI收割
来源：自动化研究所
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