The Academic Perspective Procedia publishes Academic Platform symposiums papers as three volumes in a year. DOI number is given to all of our papers.
Publisher : Academic Perspective
Journal DOI : 10.33793/acperpro
Journal eISSN : 2667-5862
[1] Boubaker, O. (2013). The inverted pendulum benchmark in nonlinear control theory: a survey. International Journal of Advanced Robotic Systems, 10(5), 233.
[2] Åström, K. J., & Hägglund, T. (1995). PID Controllers: Theory, Design, and Tuning (2nd ed.). Instrument Society of America.
[3] Boubaker, O. (2012, July). The inverted pendulum: A fundamental benchmark in control theory and robotics. In International conference on education and e-learning innovations (pp. 1-6). IEEE.
[4] Ziegler, J. G., & Nichols, N. B. (1942). Optimum settings for automatic controllers. Transactions of the ASME, 64(11), 759–768.
[5] Rithirun, C., Charean, A., & Sawaengsinkasikit, W. (2021, March). Comparison between pid control and fuzzy pid control on invert pendulum system. In 2021 9th International Electrical Engineering Congress (iEECON) (pp. 337-340). IEEE.
[6] Duru, A. S. (2023). Metaheuristic Algorithms Based PID Controller Tuning Approach for Inverted Pendulum System. Van Yüzüncü Yıl Üniversitesi Mühendislik Fakültesi Dergisi, 1(1), 37-50.
[7] Alimoradpour, S., Rafie, M., & Ahmadzadeh, B. (2022). Providing a genetic algorithm-based method to optimize the fuzzy logic controller for the inverted pendulum. Soft Computing, 26(11), 5115-5130.
[8] Dastranj, M. R., Moghaddas, M., Afghu, S. S., & Rouhani, M. (2011, May). PID control of inverted pendulum using particle swarm optimization (PSO) algorithm. In 2011 IEEE 3rd International Conference on Communication Software and Networks (pp. 575-578). IEEE.
[9] Chakraborty, K., Mukherjee, R. R., & Mukherjee, S. (2013). Tuning of PID controller of inverted pendulum using genetic algorithm. International Journal of Soft Computing and Engineering (IJSCE), 3(1), 21-24.
[10] Alhijawi, B., & Awajan, A. (2024). Genetic algorithms: Theory, genetic operators, solutions, and applications. Evolutionary Intelligence, 17(3), 1245-1256.
[11] Gad, A. G. (2022). Particle swarm optimization algorithm and its applications: a systematic review. Archives of computational methods in engineering, 29(5), 2531-2561.
[12] Mousakazemi, S. M. H. (2021). Comparison of the error-integral performance indexes in a GA-tuned PID controlling system of a PWR-type nuclear reactor point-kinetics model. Progress in Nuclear Energy, 132, 103604.
[13] Soni, Y. K., & Bhatt, R. (2013). BF-PSO optimized PID controller design using ISE, IAE, IATE and MSE error criteria. International Journal of Advanced Research in Computer Engineering & Technology (IJARCET), 2(7), 2333-2336.