CASIA OpenIR  > 复杂系统管理与控制国家重点实验室  > 先进机器人
Back-propagation neural network based predictive control for biomimetic robotic fish
Wang, Ming1,2; Yu, Junzhi1; Tan, Min1; Yang, Qinghai1; Wang Ming
2008
Conference Name27th Chinese Control Conference, CCC
Source PublicationChinese Control Conference, CCC
Conference DateJuly 16, 2008 - July 18, 2008
Conference PlaceKunming, Yunnan, China
AbstractThis paper presents a practical swimming data prediction method for a free-swimming, three-link robotic fish. Since a full hydrodynamic model for fish swimming is very complex and intractable, the primitive swimming data generated by a Central Pattern Generator controller is fed into a Back-Propagation Neural Network (BPNN) for trimming. After the process of training, the BPNN is able to predict the actual swimming data for various swimming patterns without dynamic modeling. Preliminary simulation and experimental results on swimming control show the effectiveness of the proposed prediction method as well as its potential for other flexible link-based robots.
KeywordBiomimetic Robotic Fish Central Pattern Generator Back-propagation Neural Network Predictive Control Motion Control
Document Type会议论文
Identifierhttp://ir.ia.ac.cn/handle/173211/13061
Collection复杂系统管理与控制国家重点实验室_先进机器人
Corresponding AuthorWang Ming
Affiliation1. Laboratory of Complex Systems and Intelligence Science, Institute of Automation, Chinese Academy of Sciences, Beijing 100190, China
2. School of Information and Electric Engineering, Shandong Jianzhu University, Jinan 250101, China
Recommended Citation
GB/T 7714
Wang, Ming,Yu, Junzhi,Tan, Min,et al. Back-propagation neural network based predictive control for biomimetic robotic fish[C],2008.
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