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http://dx.doi.org/10.5302/J.ICROS.2014.14.8023

NN-based Adaptive Control for a Skid-type Autonomous Unmanned Ground Vehicle  

Shin, Jongho (Agency for Defense Development)
Joo, Sanghyun (Agency for Defense Development)
Publication Information
Journal of Institute of Control, Robotics and Systems / v.20, no.12, 2014 , pp. 1278-1283 More about this Journal
Abstract
This study proposes a NN (Neural Networks)-based adaptive control method for a 6X6 skid-type UGV (Unmanned Ground Vehicle) with 6 in-wheel motors. The UGV experiences lots of uncertainties and, thus, the control performance can degrade significantly without a compensation of the unknown terms. To improve the control performance of the UGV, the NN is utilized to design the adaptive controller. Then, the designed overall force and moment are optimally distributed into 6 traction forces with the assumption that six vertical forces of the UGV are known exactly, because the six traction forces are original source to be excited to the UGV to move. Finally, numerical simulations with the TruckSim model are performed to validate the effectiveness of the proposed approach.
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Times Cited By KSCI : 2  (Citation Analysis)
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