Fuzzy Sliding Mode Control with Moving Sliding Surface of Rotary Inverted Pendulum

Yıl 2022, Cilt: 8 Sayı: 3, 355 - 369, 25.09.2022

Muhammet Aydın , Oğuz Yakut

https://doi.org/10.28979/jarnas.1015366

Cited By: 1

Öz

In this study, considering the dynamic equations of the rotary inverted pendulum system and the motor dynamics, pendulum angle is controlled with fuzzy logic sliding mode control method which has moving sliding surface using state variables in Matlab program. The sliding surface of sliding mode control method is selected as moving. A fuzzy logic structure is used to calculate the slope of slip surface. The boundary values of the membership functions in the fuzzy logic structure have been optimized using genetic algorithm codes in Matlab program. The sum of the squares of the errors is preferred as the objective function. Inputs of the fuzzy logic structure are the error of the pendulum angle and the derivative of pendulum angle error. In the fuzzy logic structure, the slope of sliding surface of sliding mode control structure is obtained as an output. From the results, it was seen that the pendulum angle reached the desired reference value around the first second and the error was approximately zero. In addition, it has been observed that the motor torque value is at the levels of 20 Nm and the motor current value is at the levels of 3 ampers. It has been obtained from the results that the motor values are at reasonable levels close to the values in practical applications. When the motor is selected according to these obtained values, there won't be a problem with the implementation of this control method in real-time applications of the rotary inverted pendulum system

Anahtar Kelimeler

Fuzzy logic control, Motor model, Moving sliding mode control, Rotary inverted pendulum, Sliding surface

Kaynakça

• Altinoz, O. T., Yilmaz, A. E., & Weber, G. W. (2010). Chaos particle swarm optimized PID controller for the inverted pendulum system. In 2nd international conference on engineering optimization.
• Awtar, S., King, N., Allen, T., Bang, I., Hagan, M., Skidmore, D., & Craig, K. (2002). Inverted pendulum systems: rotary and arm-driven-a mechatronic system design case study. Mechatronics, 12(2), 357-370.
• Aydin, M., Yakut, O., & Tutumlu, H. (2019). Implementation of the Network-Based Moving Sliding Mode Control Algorithm to the Rotary Inverted Pendulum System. Journal of Engineering and Technology, 3(1), 32-41.
• Bogdanov, A. (2004, Aralık) Optimal control of a double inverted pendulum on a cart, Health and Science University Technical Report. Bugeja, M. (2003, September). Non-linear swing-up and stabilizing control of an inverted pendulum system. In The IEEE Region 8 EUROCON 2003. Computer as a Tool. (Vol. 2, pp. 437-441). IEEE.
• Edwards, C., & Spurgeon, S. (1998). Sliding mode control: theory and applications. Crc Press.
• Hassanzadeh, I., & Mobayen, S. (2008). PSO-based controller design for rotary inverted pendulum system. Journal of Applied Sciences, 8(16), 2907-2912.
• Horikawa, S. I., Yamaguchi, M., Furuhashi, T., & Uchikawa, Y. (1995). Fuzzy Control for Inverted Pendulum Using Fuzzy Neural Networks. J. Robotics Mechatronics, 7(1), 36-44. Jia, N., & Wang, H. (2008). Nonlinear Control of an Inverted Pendulum System Based on Sliding-Mode Method. ACTA Analysis Functionalis Applicate, 10(3), 234-237.
• Khanesar, M. A., Teshnehlab, M., & Shoorehdeli, M. A. (2007, June). Sliding mode control of rotary inverted pendulm. In 2007 Mediterranean Conference on Control & Automation (pp. 1-6). IEEE.
• Krishen, J., & Becerra, V. M. (2006, October). Efficient fuzzy control of a rotary inverted pendulum based on LQR mapping. In 2006 IEEE Conference on Computer Aided Control System Design, 2006 IEEE International Conference on Control Applications, 2006 IEEE International Symposium on Intelligent Control (pp. 2701-2706). IEEE.
• Kuo, T. C., Huang, Y. J., & Hong, B. W. (2009, July). Adaptive PID with sliding mode control for the rotary inverted pendulum system. In 2009 IEEE/ASME International Conference on Advanced Intelligent Mechatronics (pp. 1804-1809). IEEE.
• Stimac, A. K. (1999). Standup and stabilization of the inverted pendulum (Doctoral dissertation, Massachusetts Institute of Technology, Dept. of Mechanical Engineering).
• Sugie, T., & Fujimoto, K. (1998). Controller design for an inverted pendulum based on approximate linearization. International Journal of Robust and Nonlinear Control: IFAC‐Affiliated Journal, 8(7), 585-597.
• Sukontanakarn, V., & Parnichkun, M. (2009). Real-time optimal control for rotary inverted pendulum. American journal of applied sciences, 6(6), 1106.
• Wang, W. (2009). Adaptive fuzzy sliding mode control for inverted pendulum. In Proceedings. The 2009 International Symposium on Computer Science and Computational Technology (ISCSCI 2009) (p. 231). Academy Publisher.
• Yan, Q. (2003, December). Output tracking of underactuated rotary inverted pendulum by nonlinear controller. In 42nd IEEE International Conference on Decision and Control (IEEE Cat. No. 03CH37475) (Vol. 3, pp. 2395-2400). IEEE.
• Young, K. D., Utkin, V. I., & Ozguner, U. (1999). A control engineer's guide to sliding mode control. IEEE transactions on control systems technology, 7(3), 328-342.
• Zadeh, I. H., & Mobayen, S. (2008). PSO-based controller for balancing rotary inverted pendulum. J. AppliedSci, 16, 2907-2912.
• Zhong, W., & Rock, H. (2001, September). Energy and passivity based control of the double inverted pendulum on a cart. In Proceedings of the 2001 IEEE International Conference on Control Applications (CCA'01)(Cat. No. 01CH37204) (pp. 896-901). IEEE.