Motion Control of Muck Removal Manipulator of Tunnel Boring Machine
The muck removal manipulator uses a valve-controller hydraulic cylinder system with modeling uncertainty and strong nonlinear characteristics.To improve the accuracy of the motion of the muck removal manipulator,this research proposes a trajectory tracking control method.Based on the scaled test bench model of muck removal manipulator,a kinematic model is established using the modified D-H method,a nonlinear coupled dynamics model of muck removal manipulator is established based on the Lagrangian.To address the modeling uncertainty of dynamic models,an radial basis function neural network is used to approximate the unknown terms in the model,and the weights in the neural network are adjusted online using adaptive methods.Finally,a simulation model based on the scale test bench data is used to validate the theory proposed.The results show that the method can ensure that the trajectory tracking process has small errors.
万方数据
维普
