Authors

1 Department of Control and Systems Engineering, University of Technology, Baghdad, Iraq

2 b Department of Control and Systems Engineering, University of Technology, Baghdad, Iraq

Abstract

The inverted pendulum is a standard classical problem in the branch of
control and systems. If a cart is bushed by force then its position and angle
of the pendulum will be changed. Several controllers may employed,
keeping the pendulum arm upright by controlling at the cart location. In
this search paper, the fuzzy-like PID (FPID) controller has been used to
control the inverted pendulum, and the parameters of the controller are
tuned with several evolutionary optimization algorithms like a genetic
algorithm (GA), ant colony optimization (ACO), and social spider
optimization (SSO.) The result of tuned FPID with evolutionary
optimization is compared with conventional PID, and it shows that FPID
with SSO has been given the best result.

Keywords

Main Subjects

[1] M. Magdy, A. El-Marhomy, M. A. Attia, “Modeling of inverted pendulum system with gravitational search algorithm optimized controller,” Dept. of Eng. Physics and Math., Faculty of Eng., Ain Shams University, Cairo, Egypt, January 2019.
[2] I. R. Ahmad, Y. Samer, H. Al-Rizzo, “Fuzzy-logic control of an inverted pendulum on a cart,” Dept. of Mechanical, Materials and Manufacturing Eng., The Univ. of Nottingham, Malaysia Campus, Malaysia, July 2017.
[3] Y. Becerikli, B.K. Celik, “Fuzzy control of inverted pendulum and concept of stability using Java. Application,” Kocaeli Univ., Turkey, 15 December 2006
[4] M. A. Saeed, S. T. H. Rizvi and M. Y. Javed, “Optimize algorithm for motion control of inverted pendulum with real time assessment using MATLAB,” Dept. of Electrical Eng., Univ. of Central Punjab, Lahore, Pakistan.
[5] P. Strakoš and Tůma, “Mathematical modelling and controller design of inverted pendulum,” Dept. of Control Systems and Instrumentation, VŠB-TU Ostrava, Czech Republic, IEEE, 2017.
[6] P. warak, “Mathematical modeling of inverted pendulum with disturbance input,” Student, M.E. Control Systems, K.K.W. COE. &Research, Nashik, India, 2013.
[7] C. Wang, G. Yin, C. Liu, W. Fu, “Design and simulation of inverted pendulum system based on the fractional PID controller,” Changchun Univ. of Science and Technology Dept. Changchun, IEEE 2016.
[8] K. M. Passino, S. Yurkovich, “Fuzzy control,” Dept. of Electrical Eng., Ohio State Univ., Addison Wesley Longman, 1997.
[9] G.V. Ochoa., J.D. Forero and L.O. Quiñones., “Fuzzy control of an inverted pendulum systems in MATLAB-Simulink,” Efficient Energy Management Research Group-Kai, Univ. of Atlántico km 7 Antigua vía Puerto, Colombia, 2018.
[10] J. Wang., “Simulation studies of inverted pendulum based on PID controllers,” Hangzhou. Dianzi. Univ., China, August 2010.
[11] S. M. Abuelenin, “Decomposed interval type-2 fuzzy systems with application to inverted pendulum,” Eng. Faculty, Port-Said Univ., Egypt, 2014, IEEE.
[12] A. M. El-Nagar, “Intelligent control for nonlinear inverted pendulum based on interval type-2 fuzzy PD controller”, Dept. of Industrial Electronics and Control Eng., Faculty of Electronic Engineering, Menofia Univ., Menof 32852, Egypt, November 2013.
[13] M. E. Abdela, H. M. Emara., A. Bahgat., “Interval type 2 fuzzy sliding mode control with application to inverted pendulum on a cart,” Electrical power and machines dept. Cairo Univ., Giza, Egypt, IEEE 2013.
[14] A. Çakan, F. M. Botsal, M. Tinkir, “PID control of inverted pendulum using Adams and MATLAB co-simulation,” Selçuk Univ. Mechanical Eng. Dept., Konya-Turkey, December 2016.
[15] M. A. Şen, V. Bakırcıoğlu, M. Kalyoncu, “Performances comparison of the bees algorithm and genetic algorithm for PID controller tuning,” Selçuk. Univ., Turkey, December 2016.
[16] F. Wei, G. Liangzhong, Y.J. B. Qingqing “Inverted pendulum control system based on GA optimization,” College of Mechanical Eng., South Univ. of Technology, Guangzhou, China, IEEE, 2007.
[17] M. Moghaddas, M. R. Dastranj, N. Changizi, and N. Khoori, “Design of optimal PID controller for inverted pendulum using genetic algorithm,” Control Dept., Islamic Azad Univ. of Gonabad, Iran, IJIMT, August 2012.
[18] M.A. Sen and M. Kalyoncu, “ Optimisation of a PID controller for an inverted pendulum using the bees algorithm,” Dept. of Mechanical Eng., Faculty of Eng., Univ. of Selçuk, 42250 Konya, Trukey, may 2015.
[19] M.Y. Hassan and A.A. Mahmood, “A spiking neural network controller design with VHDL based on SSO algorithm for inverted pendulum,” Dept. of Control and Systems, Univ. of Technology, Iraq, IJESC, 2019.
[20] I. Abuiziah, N. Shakarneh, “A review of genetic algorithm optimization: operations and applications to water pipeline systems,” Dept. of Civil and Architectural Eng. Palestine Polytechnic Univ., December 2013.
[21] D.E. GoldBerg, “Genetic algorithms in search, optimization, and machine learning,” Univ. of Alabama, January 1989.
[22] S. Katiyar, I. Nasiruddin, A.Q. Ansari, “Ant colony optimization: a tutorial review,” Dept. of Electrical Eng., Millia Islamia Univ., New Delhi, August 2015.
[23] D. Wang, D. Tan, L. Liu, “Particle swarm optimization algorithm: an overview,” Zhengzhou Univ. China, January 2017.
[24] A. Luque-Chang, E. Cuevas, F. Fausto, D. Zald-var, and M. Pérez, “Social spider optimization algorithm: modifications, applications, and perspectives,” Dept. of Electronic, Univ. of Guadalajara, Mexico, 8 November 2018