Neurotechnology for Biomimetic Robots
Neurotechnology for Biomimetic Robots
pth moment stability analysis of stochastic recurrent neural networks with time-varying delays
Information Sciences: an International Journal
Finding the differential characteristics of block ciphers with neural networks
Information Sciences: an International Journal
Improving artificial neural networks' performance in seasonal time series forecasting
Information Sciences: an International Journal
Macro-continuous computed torque algorithm for a three-dimensional eel-like robot
IEEE Transactions on Robotics
Geometric Optimization of Relative Link Lengths for Biomimetic Robotic Fish
IEEE Transactions on Robotics
Geometric Methods for Modeling and Control of Free-Swimming Fin-Actuated Underwater Vehicles
IEEE Transactions on Robotics
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This paper focuses on the modeling of undulation propulsion and a neural network (NN) yaw controller based on this model. First, because of the importance of the first link's oscillation in yaw control, a motion model of free swimming was built based on the Lagrangian function, and the coupled dynamic and kinematic functions were calculated based on the relation between the generalized force and the fluid force. Second, a neural network was trained through the data generated from this model to obtain a predictive yaw controller that could control the orientation by the different offsets of each link. Finally, simulations were conducted to demonstrate the performance of the controller.