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Intelligent Adaptive Motion Control for Two Types of Electric Unicycles
|關鍵字:||自適應控制;倒逆步;順滑模態控制;模糊小腦模型控制器;小波模糊小腦模型控制器;adaptive control;backstepping;sliding mode control;fuzzy cerebra model articulation controller;wavlet fuzzy cerebra model articulation controller;electric unicycle||引用:|| F. Grasser, A.D' Arrigo, and S. Colombi, 'JOE: Amobile, inverted pendulum,' IEEE Transactions on Industrial Electronics, vol. 49, no.1, pp.107-114, February 2002.  D. Voth, 'Segway to the future,' Intelligent System, IEEE [see also IEEE Intelligent System and Their Applications], vol.20, no.3, pp.5-8, May-June 2005.  C. C. Tsai, S. C. Lin and W. L. Luo, 'Adaptive steering of a self-balancing two- wheeled transport,' in Proc. 2006 CACS Automatic Control, Tasmsui, Taiwan, November 10-11, 2006.  C. C. Tsai, H. C. Huang, S. C. Lin, 'Adaptive neural network control fo a self-balancing Two-wheeled Scooter,' IEEE Transactions on Industrial Electronics, vol. 57, no.4, pp. 1420-1428, April 2010.  Focus Designs, Inc. http://focusdesigns.com/, [Online], 2014. 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Tsai, System Design and Control of an Electric Two-Wheeled Robotic Vehicle, MS Thesis, Department of Electrical Engineering, National Chung Hsing University, June, 2012.  C. C. Tsai, and H. S. Yap, 'Intelligent adaptive motion control for uncertain seatless electric unicycle,' in Proc. of 2013 13th International Conference on Automation Control, and Systems (ICCAS 2013), Kimdaejung conventional center, Kwangju, Korea, 2013.  C. C. Tsai and H. S. Yap, 'Intelligent Adaptive Steering Control Using IT2FNN for Uncertain Seatless Electric Unicycle.' in Proc. of 2013 International Conference on Fuzzy : Theory and it Applications, Nation Taiwan University of Science and Technology, Taipei, Taiwan, Dec 6-8, 2013.||摘要:||
This dissertation presents techniques and methodologies for system design, mathematical modeling, and intelligent adaptive motion control for two types of electric unicycles. A mechatronic method is used to accomplish system design, key components and control architecture of two types of experimental electric unicycles. Mathematic models of the vehicles are established by using Lagrangian mechanics and taking into account different riders and terrain surfaces. For the purpose of achieving self-balancing and speed control goals, we propose four types of controllers: linear quadratic regulator (LQR) control, nonlinear adaptive steering control with fuzzy cerebra model articulation controller (CMAC), adaptive steering control with wavelet fuzzy CMAC (WFCMAC), and direct adaptive WFCMAC control. The asymptotic stabilities of the proposed four controllers are proven by Lyapunov stability theory and Barbara lemma. The effectiveness and merits of the proposed controllers are well exemplified by conducting computer simulations on experimental electric unicycles. Comparative studies via simulations also show that the proposed controllers outperform other existing controllers. Many riding experiments are carried out to demonstrate the performance and applicability of the proposed controllers together with both types of laboratory-built experimental electric unicycles.
|Appears in Collections:||電機工程學系所|
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