TY - GEN

T1 - Solving the forward kinematics problem of a parallel kinematic machine using the neural network method

AU - Zhang, Dan

AU - Shi, Qi

AU - Lei, Jianhe

PY - 2010

Y1 - 2010

N2 - In this paper, the forward kinematic problem of a 3-DOF asymmetrical parallel kinematic machine has been solved using multi-layered neural network method. The mathematical expression of the multi-layered feed forward neural networks with back-propagation is introduced. Neural network of the 3-DOF parallel manipulator was trained based on the data generated from the closed-form inverse kinematic solution. Levenberg-Marquardt algorithm is applied to train the moderate-sized feed forward neural network, which leads to the fastest convergence of the network. After the learning stage, the network was tested on a random selected data and the simulation results showed that the neural network configuration can receive the expected accuracy of the parallel manipulator. The optimal artificial neural network model of the 3-DOF parallel manipulator has been found with tan-sigmoid transfer function for the middle hidden layer. The trained neural network model of the forward kinematics of the 3-DOF parallel manipulator can be used for real-time control purpose.

AB - In this paper, the forward kinematic problem of a 3-DOF asymmetrical parallel kinematic machine has been solved using multi-layered neural network method. The mathematical expression of the multi-layered feed forward neural networks with back-propagation is introduced. Neural network of the 3-DOF parallel manipulator was trained based on the data generated from the closed-form inverse kinematic solution. Levenberg-Marquardt algorithm is applied to train the moderate-sized feed forward neural network, which leads to the fastest convergence of the network. After the learning stage, the network was tested on a random selected data and the simulation results showed that the neural network configuration can receive the expected accuracy of the parallel manipulator. The optimal artificial neural network model of the 3-DOF parallel manipulator has been found with tan-sigmoid transfer function for the middle hidden layer. The trained neural network model of the forward kinematics of the 3-DOF parallel manipulator can be used for real-time control purpose.

KW - Back-propagation

KW - Forward/inverse kinematics

KW - Multilayer perceptron (MLP)

KW - Neural network

KW - Parallel kinematic machine

UR - http://www.scopus.com/inward/record.url?scp=78149372914&partnerID=8YFLogxK

M3 - Conference article published in proceeding or book

AN - SCOPUS:78149372914

SN - 0872638685

SN - 9780872638686

T3 - Transactions of the North American Manufacturing Research Institution of SME

SP - 727

EP - 733

BT - Transactions of the North American Manufacturing Research Institution of SME 2010, NAMRI/SME

T2 - 38th Annual North American Manufacturing Research Conference, NAMRC 38

Y2 - 25 May 2010 through 28 May 2010

ER -