Knowledge Commons of Institute of Automation,CAS
Trajectory Tracking Control of Omnidirectional Wheeled Mobile Manipulators: Robust Neural Network-Based Sliding Mode Approach | |
Xu, Dong1,2; Zhao, Dongbin1; Yi, Jianqiang1; Tan, Xiangmin1 | |
发表期刊 | IEEE TRANSACTIONS ON SYSTEMS MAN AND CYBERNETICS PART B-CYBERNETICS |
2009-06-01 | |
卷号 | 39期号:3页码:788-799 |
文章类型 | Article |
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. |
关键词 | Omnidirectional Mobile Manipulators Robust Neural Network (Nn) Sliding Mode Control (Smc) Trajectory Tracking Control Uncertainties |
WOS标题词 | Science & Technology ; Technology |
关键词[WOS] | SYSTEMS ; ROBOTS ; MOTION |
收录类别 | SCI |
语种 | 英语 |
WOS研究方向 | Automation & Control Systems ; Computer Science |
WOS类目 | Automation & Control Systems ; Computer Science, Artificial Intelligence ; Computer Science, Cybernetics |
WOS记录号 | WOS:000266069600016 |
引用统计 | |
文献类型 | 期刊论文 |
条目标识符 | http://ir.ia.ac.cn/handle/173211/3590 |
专题 | 多模态人工智能系统全国重点实验室_平行智能技术与系统团队 |
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 |
第一作者单位 | 中国科学院自动化研究所 |
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. |
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