CASIA OpenIR  > 复杂系统管理与控制国家重点实验室  > 先进机器人
Adaptive Neural Network Control of an Aerial Work Platform’s arm
Jia, Pengxiao; Li, En; Liang, Zize; Qiang, Yanhui; Pengxiao Jia; En Li; Zizhe Liang; Yanhui Qiang
2012
Conference NameThe 10th World Congress on Intelligent Control and Automation (WCICA)
Source PublicationProceedings of the 10th World Congress on Intelligent Control and Automation (WCICA)
Conference Date2012
Conference PlaceBeijing
Other AbstractAn aerial work platform (AWP) is a type of off highway vehicle with a long beam to provide temporary access to inaccessible areas [1]. The motivation of the research is to increase its productivity, safety and reduce the manipulation complexity during the operation process. In this paper, a simplified two-link model of AWP's arm is given. The control scheme based on neural network modeling technology is employed to steer the AWP's arm to track the desired trajectories asymptotically, which requires neither the evaluation of inverse dynamical model nor the time-consuming training process. The simulation results validate the effectiveness of the proposed approach.
KeywordNeural Networks Trajectory Adaptive Systems Adaptation Models Robots Mathematical Model Aerospace Electronics
Indexed ByEI
Document Type会议论文
Identifierhttp://ir.ia.ac.cn/handle/173211/11083
Collection复杂系统管理与控制国家重点实验室_先进机器人
Corresponding AuthorPengxiao Jia; En Li; Zizhe Liang; Yanhui Qiang
Recommended Citation
GB/T 7714
Jia, Pengxiao,Li, En,Liang, Zize,等. Adaptive Neural Network Control of an Aerial Work Platform’s arm[C],2012.
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