Fuzzy logic control vs. conventional PID control of an inverted pendulum robot

This paper addresses some of the potential benefits of using fuzzy logic controllers to control an inverted pendulum system. The stages of the development of a fuzzy logic controller using a four input Takagi-Sugeno fuzzy model were presented. The main idea of this paper is to implement and optimize fuzzy logic control algorithms in order to balance the inverted pendulum and at the same time reducing the computational time of the controller. In this work, the inverted pendulum system was modeled and constructed using Simulink and the performance of the proposed fuzzy logic controller is compared to the more commonly used PID controller through simulations using Matlab. Simulation results show that the fuzzy logic controllers are far more superior compared to PID controllers in terms of overshoot, settling time and response to parameter changes.

[1]  Kazuo Tanaka,et al.  An approach to fuzzy control of nonlinear systems: stability and design issues , 1996, IEEE Trans. Fuzzy Syst..

[2]  Naim A. Kheir,et al.  Control system design , 2001, Autom..

[3]  Bernard Friedland,et al.  Control Systems Design , 1985 .

[4]  Mohamed I. El-Hawwary,et al.  Adaptive Fuzzy Control of the Inverted Pendulum Problem , 2006, IEEE Transactions on Control Systems Technology.

[5]  Johnny Steven Lam Control of an Inverted Pendulum , 2004 .

[6]  John C. Tang,et al.  A Comparative Study of Fuzzy Logic and Classical Control with EPICS[Experimental Physics and Industrial Control System] , 1995 .

[7]  Sergey V. Drakunov,et al.  Sliding mode control of an inverted pendulum , 1996, Proceedings of 28th Southeastern Symposium on System Theory.

[8]  T. Yamakawa Fuzzy logic hardware systems , 1989, Symposium 1989 on VLSI Circuits.

[9]  Hong Li,et al.  Fuzzy control of a double inverted pendulum using two closed loops , 2004, Fifth World Congress on Intelligent Control and Automation (IEEE Cat. No.04EX788).

[10]  Hosein Marzi Multi-Input Fuzzy control of an inverted pendulum using an armature controlled DC motor , 2005, Robotica.

[11]  M.A. Lee,et al.  Integrating design stage of fuzzy systems using genetic algorithms , 1993, [Proceedings 1993] Second IEEE International Conference on Fuzzy Systems.

[12]  Li Xu,et al.  Development of inverted pendulum system and fuzzy control based on MATLAB , 2004, Fifth World Congress on Intelligent Control and Automation (IEEE Cat. No.04EX788).

[13]  H. Takagi,et al.  Integrating Design Stages of Fuzzy Systems using Genetic Algorithms 1 , 1993 .

[14]  Katsuhisa Furuta,et al.  Control of unstable mechanical system Control of pendulum , 1976 .