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Design of Fuzzy Logic Control System for Segway Type Mobile Robots
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 Title & Authors
Design of Fuzzy Logic Control System for Segway Type Mobile Robots
Kwak, Sangfeel; Choi, Byung-Jae;
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Studies on the control of inverted pendulum type systems have been widely reported. This is because this type of system is a typical complex nonlinear system and may be a good model to verify the performance of a proposed control system. In this paper, we propose the design of two fuzzy logic control systems for the control of a Segway mobile robot which is an inverted pendulum type system. We first introduce a dynamic model of the Segway mobile robot and then analyze the system. We then propose the design of the fuzzy logic control system, which shows good performance for the control of any nonlinear system. In this paper, we here design two fuzzy logic control systems for the position and balance control of the Segway mobile robot. We demonstrate their usefulness through simulation examples. We also note the possibility of simplifying the design process and reducing the computational complexity. This possibility is the result of the skew symmetric property of the fuzzy rule tables of the system.
Inverted Pendulum System;Segway Mobile Robot;Fuzzy Logic Control System;Position Control;Balance Control;
 Cited by
Design of Simple-Structured Fuzzy Logic Systems for Segway-Type Mobile Robot, The International Journal of Fuzzy Logic and Intelligent Systems, 2015, 15, 4, 232  crossref(new windwow)
Robust Control for the Segway with Unknown Control Coefficient and Model Uncertainties, Sensors, 2016, 16, 7, 1000  crossref(new windwow)
Investigating the Impact of Possession-Way of a Smartphone on Action Recognition, Sensors, 2016, 16, 6, 812  crossref(new windwow)
The SEGWAY website. [Online]. Available:

S.-H. Lee and S.-Y. Rhee, “Dynamic modelling of a wheeled inverted pendulum for inclined road and changing its center of gravity,” J. of Korean Institute of Intelligent Systems, vol. 22, no. 1, pp. 69-74, 2012. crossref(new window)

B.-J. Choi and S. Jin, “Design of Simple-structured Fuzzy Logic System based Driving Controller for Mobile Robot,” J. of Korean Institute of Intelligent Systems, vol.22, no.1, 2012.2.

H. W. Kim and S. Jung, “Fuzzy Logic Application to a Two-wheel Mobile Robot for Balancing Control Performance,” Int. J. of Fuzzy Logic and Intelligent Systems, vol.12, no.2, 2012.6.

J. H. Park, “Fuzzy-logic zero-moment-point trajectory generation for reduced trunk motion of biped robots,” Fuzzy Set Techniques for Intelligent Robotic Systems, vol. 134, no. 1, pp. 189-203, Feb. 2003.

H. Ha and J. Lee, “A control of mobile inverted pendulum using single accelerometer,” J. of Institute of Control, Robotics and Systems, vol. 16, no. 5, 2010

S. W. Nawawi, M. N. Ahmad, and J. H. S. Osman, “Control of two-wheels inverted pendulum mobile robot using full order sliding mode control,” Proc. of International Conference on Man-Machine System, Lankawi, Malaysia, Sep. 2006.

P. Axelsson and Y. Jung, Lego Segway Project Report, Technical Report from Automatic Control at Linkopings Universitet, Division of Automatic Control, 2011.

J. S. Noh, G. H. Lee, and S. Jung, “Position control of amobile inverted pendulum system using radial basis function network,” Int. J. of Control Automation and Systems, vol. 8, no. 1, 2010.

J. Huang, Z. Guan, T. Matsuno, T. Fukuda, and K. Sekiyama, “Sliding-Mode Velocity Control of Mobile WheeledInverted-Pendulum Systems,” IEEE Trans. on Robotics, vol. 26, no. 4, 2010.

T. Jin, “Obstacle Avoidance of Mobile Robot Based on Behavior Hierarchy by Fuzzy Logic,” Int. J. of Fuzzy Logic and Intelligent Systems, vol.12, no.3, 2012.9

L. Mao, J. Huang, F. Ding, and Y. Wang, “Velocity control of mobile wheeled inverted pendulum,” Int. J. of Modelling Identification and Control, vol. 19, no. 1, 2013.

X. Xiong and B.-J. Choi, “Comparative Analysis of Detection Algorithms for Corner and Blob Features in Image Processing,” Int. J. of Fuzzy Logic and Intelligent Systems, vol.13, no.4, 2013.

B.-H. Kim, “Analysis of Balance of Quadrupedal Robotic Walk using Measure of Balance Margin,” Int. J. of Fuzzy Logic and Intelligent Systems, vol.13, no.2, 2013.

K. D. Do, and G. Seet, “Motion Control of a Two-Wheeled Mobile Vehicle with an Inverted Pendulum,” J. of Intelligent and Robotic Systems, vol. 60, no. 3-4, 2010.

H.-G. Nguyen, W.-H. Kim, and J.-H. Shin, “A Study on an Adaptive Robust Fuzzy Controller with GAs for Path Tracking of a Wheeled Mobile Robot,” Int. J. of Fuzzy Logic and Intelligent Systems, vol.10, no.1, 2010.3.