Motion control of deep sea vehicle 'OTOHIME': modeling with neural network

摘要

Deep sea survey vehicle 'OTOHIME' is one of the underwater vehicle owned in JAMSTEC and its automatic navigation system is developing now. To construct the control system, vehicle motion should be modeled at first. In this study, we treated a dynamic equation model and two types of neural network models and compared their performance. The latter showed rather better results than the former. Then we decide to use the neural network model to design the control system as the next step.