Please use this identifier to cite or link to this item: http://hdl.handle.net/11455/44551
標題: Adaptive Neural Network Control of a Self-Balancing Two-Wheeled Scooter
作者: Tsai, C.C.
蔡清池
Huang, H.C.
Lin, S.C.
關鍵字: Adaptive control;neural network;radial basis function;self-balancing;two-wheeled robot;inverted pendulum;mobile;front
Project: Ieee Transactions on Industrial Electronics
期刊/報告no:: Ieee Transactions on Industrial Electronics, Volume 57, Issue 4, Page(s) 1420-1428.
摘要: 
This paper presents an adaptive control using radial-basis-function neural networks (RBFNNs) for a two-wheeled self-balancing scooter. A mechatronic system structure of the scooter driven by two dc motors is briefly described, and its mathematical modeling incorporating two frictions between the wheels and the motion surface is derived. By decomposing the overall system into two subsystems (yaw motion and mobile inverted pendulum), one proposes two adaptive controllers using RBFNN to achieve self-balancing and yaw control. The performance and merit of the proposed adaptive controllers are exemplified by conducting several simulations and experiments on a two-wheeled self-balancing scooter.
URI: http://hdl.handle.net/11455/44551
ISSN: 0278-0046
DOI: 10.1109/tie.2009.2039452
Appears in Collections:電機工程學系所

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