DocumentCode :
2961593
Title :
Control of inverted pendulum system using a neuro-fuzzy controller for intelligent control education
Author :
Lee, Geun Hyeong ; Jung, Seul
Author_Institution :
Mechatron. Eng. Dept., Chunganm Nat. Univ., Daejeon
fYear :
2008
fDate :
5-8 Aug. 2008
Firstpage :
965
Lastpage :
970
Abstract :
This article presents the implementation of control of an inverted pendulum system by using the neuro-fuzzy network. The inverted pendulum system has been built in the educational kit whose purpose is to educate control engineers in both undergraduate students and graduate students. The inverted pendulum system is known as a nonlinear system whose goal is to maintain the balance of the pendulum while tracking a desired position of the cart. The Takagi-Sugeno (T-S) neuro-fuzzy control scheme is used to control the system. The back-propagation learning algorithm for the T-S neuro-fuzzy network is derived for on-line learning and control. The control algorithm has been embedded on a DSP 2812 board to achieve the real-time control performance. Experimental results show that successful control performances of both balancing and tracking the position for the inverted pendulum system.
Keywords :
backpropagation; control engineering education; fuzzy control; fuzzy neural nets; intelligent control; learning (artificial intelligence); neurocontrollers; nonlinear control systems; DSP 2812 board; Takagi-Sugeno neuro-fuzzy control scheme; backpropagation learning algorithm; graduate students; intelligent control education; inverted pendulum system; nonlinear system; undergraduate students; Adaptive control; Communication system control; Control systems; Fuzzy logic; Fuzzy neural networks; Intelligent control; Intelligent robots; Mechatronics; Neural networks; Programmable control; Neuro-fuzzy controller; intelligent control education; inverted pendulum;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Mechatronics and Automation, 2008. ICMA 2008. IEEE International Conference on
Conference_Location :
Takamatsu
Print_ISBN :
978-1-4244-2631-7
Electronic_ISBN :
978-1-4244-2632-4
Type :
conf
DOI :
10.1109/ICMA.2008.4798889
Filename :
4798889
Link To Document :
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