DocumentCode
3244595
Title
Inverse Dynamic model identification of 2-axes PAM robot arm using neural MIMO NARX model
Author
Anh, H.P.H.
Author_Institution
Electr. & Electron. Dept., Ho Chi Minh City Univ. of Technol., Ho Chi Minh City, Vietnam
fYear
2009
fDate
14-17 July 2009
Firstpage
1282
Lastpage
1287
Abstract
In this paper, a novel inverse dynamic MIMO NARX model is used for modeling and identifying simultaneously both of joints of the prototype 2-axes PAM robot arm. The contact force variations and highly nonlinear coupling features of both links of the 2-axes PAM system are modeled thoroughly through an inverse neural MIMO NARX model-based identification process using experiment input-output training data. For the first time, the dynamic inverse neural MIMO NARX model of the 2-axes PAM robot arm has been investigated. The results show that the neural inverse dynamic MIMO NARX model trained by back propagation learning algorithm yields outstanding performance and perfect accuracy.
Keywords
MIMO systems; artificial organs; autoregressive processes; backpropagation; force control; identification; manipulator dynamics; medical robotics; neurocontrollers; nonlinear control systems; nonlinear dynamical systems; patient rehabilitation; pneumatic control equipment; 2-axes PAM robot arm system; back propagation learning algorithm; contact force control; input-output training data; inverse neural dynamic MIMO NARX model-based identification; nonlinear coupling feature; pneumatic artificial muscle; rehabilitation robot; Force control; Friction; Impedance; Intelligent robots; Inverse problems; MIMO; Manipulator dynamics; Medical treatment; Rehabilitation robotics; Robust control; 2-axes PAM robot arm; identification; modeling; neural Inverse Dynamic MIMO NARX model; pneumatic artificial muscle (PAM);
fLanguage
English
Publisher
ieee
Conference_Titel
Advanced Intelligent Mechatronics, 2009. AIM 2009. IEEE/ASME International Conference on
Conference_Location
Singapore
Print_ISBN
978-1-4244-2852-6
Type
conf
DOI
10.1109/AIM.2009.5229833
Filename
5229833
Link To Document