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http://dx.doi.org/10.5302/J.ICROS.2013.13.8014

Adaptive Control for Lateral Motion of an Unmanned Ground Vehicle using Neural Networks  

Shin, Jongho (Agency for Defense Development)
Huh, Jinwook (Agency for Defense Development)
Choe, Tokson (Agency for Defense Development)
Kim, Chonghui (Agency for Defense Development)
Joo, Sanghyun (Agency for Defense Development)
Publication Information
Journal of Institute of Control, Robotics and Systems / v.19, no.11, 2013 , pp. 998-1003 More about this Journal
Abstract
This study proposes an adaptive control algorithm for lateral motion of a UGV (Unmanned Ground Vehicle) using an NN (Neural Networks). The lateral motion of the UGV can be corrupted with various uncertainties such as side slip. In order to compensate the performance degradation of the UGV under various uncertainties, an NN-based adaptive control is designed by utilizing a virtual control concept. Since both the drift and input gain terms are uncertain, the proposed method adapts the whole terms related to the difference between the nominal and real systems. To avoid a singularity problem with the adaptive control, the affine property of the UGV dynamic model is utilized and the overall closed-loop stability is analyzed rigorously. Finally, numerical simulations using Carsim are performed to validate the effectiveness of the proposed scheme.
Keywords
UGV (Unmanned Ground Vehicle); NN (Neural Networks); adaptive control; singularity problem;
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