Hybrid fuzzy control of the inverted pendulum via vertical forces

In this article, we look at the excellent effect of vertical force as regards the stabilization of the inverted pendulum (IP) and demonstrate how the fuzzy control design methodology can be used to construct a hybrid fuzzy control system that incorporates PD control into a Takagi–Sugeno fuzzy control structure for stabilizing the IP via a vertical force. By gaining an intuitive understanding of the dynamics of the IP, the IP state space is fuzzily divided into six regions. In each region, a PD controller is designed to satisfy the stability conditions obtained by Lyapunov's direct and indirect methods. It shows that the proposed hybrid fuzzy control scheme provides a more flexible and intuitive way to stabilize the IP via a vertical force. © 2005 Wiley Periodicals, Inc. Int J Int Syst 20: 195–211, 2005.

[1]  William S. Levine,et al.  The Control Handbook , 2005 .

[2]  Sang Moo Lee,et al.  Balancing of an inverted pendulum with a kinematically redundant robot , 1999, Proceedings 1999 IEEE/RSJ International Conference on Intelligent Robots and Systems. Human and Environment Friendly Robots with High Intelligence and Emotional Quotients (Cat. No.99CH36289).

[3]  Naomi Ehrich Leonard,et al.  Controlled Lagrangians and the stabilization of mechanical systems. II. Potential shaping , 2001, IEEE Trans. Autom. Control..

[4]  V. N. Bogaevski,et al.  Algebraic methods in nonlinear perturbation theory , 1991 .

[5]  M. Fliess,et al.  Flatness and defect of non-linear systems: introductory theory and examples , 1995 .

[6]  A. Stephenson XX. On induced stability , 1908 .

[7]  Naomi Ehrich Leonard,et al.  Controlled Lagrangians and the stabilization of mechanical systems. I. The first matching theorem , 2000, IEEE Trans. Autom. Control..

[8]  Semyon Meerkov,et al.  Principle of vibrational control: Theory and applications , 1979, 1979 18th IEEE Conference on Decision and Control including the Symposium on Adaptive Processes.

[9]  Michio Sugeno,et al.  Fuzzy identification of systems and its applications to modeling and control , 1985, IEEE Transactions on Systems, Man, and Cybernetics.

[10]  D. Maravall Control and stabilization of the inverted pendulum via vertical forces , 2004 .

[11]  Da Ruan,et al.  Fuzzy control rules extraction from perception-based information using computing with words , 2002, Inf. Sci..

[12]  Stephen Yurkovich,et al.  Vibration control of a two-link flexible robot arm , 1991, Proceedings. 1991 IEEE International Conference on Robotics and Automation.

[13]  Stephen Yurkovich,et al.  Vibration control of a two-link flexible robot arm , 1993 .

[14]  Nariman Sepehri,et al.  Lyapunov stability control of inverted pendulums with general base point motion , 1998 .

[15]  Rogelio Lozano,et al.  Non-linear Control for Underactuated Mechanical Systems , 2001 .

[16]  Stelios C. A. Thomopoulos,et al.  Novel control of an inverted pendulum , 1994, Proceedings of 1994 American Control Conference - ACC '94.

[17]  D. J. Acheson,et al.  A pendulum theorem , 1993, Proceedings of the Royal Society of London. Series A: Mathematical and Physical Sciences.

[18]  Darío Maravall Gómez-Allende,et al.  Contributions to the Control and Stabilization of the Pole-Cart System , 2001, EUROCAST.

[19]  Qiong Wu Lyapunov's stability control of constrained inverted pendulums , 1999, Proceedings of the 1999 American Control Conference (Cat. No. 99CH36251).

[20]  K Furuta,et al.  Swing-up Control of Inverted Pendulum Using Pseudo-State Feedback , 1992 .

[21]  Stephen Yurkovich,et al.  Intelligent control for swing up and balancing of an inverted pendulum system , 1995, Proceedings of International Conference on Control Applications.

[22]  Shanben Chen,et al.  Robotic Welding, Intelligence and Automation , 2004 .

[23]  Li-Xin Wang,et al.  Stable adaptive fuzzy controllers with application to inverted pendulum tracking , 1996, IEEE Trans. Syst. Man Cybern. Part B.