Title :
Modeling of wave energy absorption system for underwater vehicle based on PSORBF neural networks
Author :
Zhang, Ying ; Li, Mengxin ; Xu, Ke ; Dong, Zaili
Author_Institution :
Inf. & Control Eng. Fac., Shenyang Jianzhu Univ., Shenyang, China
Abstract :
Technology of energy self-supply which can improve the work efficiency and extend the work time is significant for underwater carrier, such as underwater vehicle. As one of the renewable energy, the absorption and utilization of wave energy is always an important research field home and abroad, and energy absorption efficiency is the key. A wave energy absorption system based on inertial pendulum is presented, and dynamics equations are established. A method based on PSORBF neural network is adopted to model in time domain. The results obtained by simulation software and by neural network are compared, which validate the method used to be correct and make basis on future research.
Keywords :
energy conservation; mobile robots; particle swarm optimisation; radial basis function networks; underwater vehicles; PSORBF neural networks; dynamics equations; inertial pendulum; renewable energy; simulation software; underwater carrier; underwater vehicle; wave energy absorption system; wave energy utilization; ADAMS; PSORBF neural network; energy absorption efficiency; underwater carrier; wave energy;
Conference_Titel :
Intelligent Computing and Intelligent Systems (ICIS), 2010 IEEE International Conference on
Conference_Location :
Xiamen
Print_ISBN :
978-1-4244-6582-8
DOI :
10.1109/ICICISYS.2010.5658782