Inverse kinematics solution of the actuator based on fuzzy radial basis function neural network
Yu Qin Jin, Bingda Zhang · 2016
There are many problems for the traditional neural network, such as the solution accuracy is not high, the convergence rate is slow. In this paper, radial basis function (RBF) neural network and fuzzy logic are combined to solve the inverse kinematics of actuator. Cartesian coordinates at the singular point are used as test set. In Cartesian space, the actuator's D-H parameters are used as training sets. The simulation results show that the method has good convergence speed and high precision.