Adaptive Integrated Control for Omnidirectional Mobile Manipulators Based on Neural-Network

Xiang-min Tan, Dongbin Zhao, Jianqiang Yi and Dong Xu
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Xiang-min Tan: Chinese Academy of Sciences, China
Dongbin Zhao: Chinese Academy of Sciences, China
Jianqiang Yi: Chinese Academy of Sciences, China
Dong Xu: Sevenstar Electronics Co. Ltd., China

International Journal of Cognitive Informatics and Natural Intelligence (IJCINI), 2009, vol. 3, issue 4, 34-53

Abstract: An omnidirectional mobile manipulator, due to its large-scale mobility and dexterous manipulability, has attracted lots of attention in the last decades. However, modeling and control of such systems are very challenging because of their complicated mechanism. In this article, an unified dynamic model is developed by Lagrange Formalism. In terms of the proposed model, an adaptive integrated tracking controller, based on the computed torque control (CTC) method and the radial basis function neural-network (RBFNN), is presented subsequently. Although CTC is an effective motion control strategy for mobile manipulators, it requires precise models. To handle the unmodeled dynamics and the external disturbance, a RBFNN, serving as a compensator, is adopted. This proposed controller combines the advantages of CTC and RBFNN. Simulation results show the correctness of the proposed model and the effectiveness of the control approach.

Date: 2009
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