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| Content Provider | IEEE Xplore Digital Library |
|---|---|
| Author | Ching-Chih Tsai Cheng-Kai Chan Sen-Chung Shih Shui-Chun Lin |
| Copyright Year | 2008 |
| Description | Author affiliation: Dept. of Electr. Eng., Nat. Chung-Hsing Univ., Taichung (Ching-Chih Tsai; Cheng-Kai Chan; Sen-Chung Shih) || Dept. of Electron. Eng., Nat. Chin-Yi Univ. of Technol., Taichung (Shui-Chun Lin) |
| Abstract | This paper presents an adaptive nonlinear control using radial-basis-function neural network (RBFNN) for an electric unicycle. A mechatronic system structure of the unicycle is constructed and its simplified mathematical modeling is then established by using Newtonian mechanics and incorporating the frictions between the wheel and the terrain surface. An adaptive nonlinear control together with RBFNN is developed based on adaptive backstepping technique, in order to simultaneously achieve self-balancing and forward motion. Simulation results are conducted to illustrate feasibility and effectiveness of the proposed control method. The performance and merit of the proposed method are well exemplified by real riding test. |
| Starting Page | 2343 |
| Ending Page | 2348 |
| File Size | 358242 |
| Page Count | 6 |
| File Format | |
| ISBN | 9781424423835 |
| ISSN | 1062922X |
| DOI | 10.1109/ICSMC.2008.4811643 |
| Language | English |
| Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Publisher Date | 2008-10-12 |
| Publisher Place | Singapore |
| Access Restriction | Subscribed |
| Rights Holder | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Subject Keyword | Programmable control Adaptive control Neural networks Mechatronics Mathematical model Friction Wheels Motion control Backstepping Testing robotics transporter adaptive neural network control digital signal processing gyroscope inverted pendulum |
| Content Type | Text |
| Resource Type | Article |
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