3 accepted papers
Azimuth thrusters are widely used for controlling marine vehicles, especially, for dynamic positioning and hovering purposes. However, including azimuth thruster makes control allocation a nonlinear non-convex problem which is commonly solved using nonlinear programming methods, simplified by paring
This letter proposes an adaptive radial basis function neural network (RBF NN) based scheme for the dynamics learning and tracking control problems of a soft trunk robot. Specifically, a low-order approximate model describing the soft robot's dynamics is first derived with the finite element method
This letter presents a radial basis function neural network (RBF NN) based methodology to investigate the dynamics modeling and fault detection (FD) problems for soft robots. Finite element method (FEM) is first used to derive a mathematical model to describe the dynamics of a soft trunk robot. An a