Optimal tuning of a proportional controller for DC motor position control via Fibonacci Search Method
DOI:
https://doi.org/10.21439/jme.v4i1.88Keywords:
Optimization, Feedback control, Direct current motorAbstract
One of the advantages of using DC motors is the ease of controlling their position and speed by manipulating the input voltage. To this, feedback PID-based controllers can be used. However, adjusting these controllers can be challenging and require some reasonable effort from the controller designer. This work proposes an algorithm based on the Fibonacci Search Method to determine the optimal gain of a proportional controller applied to the position control of a DC motor. The project specifications were minimum settling time with null overshoot. The results obtained showed that the proposed method is valid for determining the Kp gain according to the plant and the conditions involved. The proposed method was compared with other optimization techniques such as Golden Section, Quasi-Newton and Grey Wolf Optimization, standing out for its simplicity of implementation, low number of iterations and fast convergence.
Downloads
References
ACHANTA, R. K.; PAMULA, V. K. DC motor speed control using PID controller tuned by jaya optimization algorithm. In: 2017 IEEE International Conference on Power, Control, Signals and Instrumentation Engineering (ICPCSI). Chennai, India: IEEE, 2017.
CHONG, E. K. P.; ZAK, S. H. An introduction to optimization. 4. ed. New Jersey: John Wiley & Sons, 2012. 624 p. ISBN 978-1-118-27901-4.
EVANS, W. R. Graphical analysis of control systems. Transactions of the American Institute of Electrical Engineers, Institute of Electrical and Electronics Engineers (IEEE), v. 67, n. 1, p. 547–551, jan 1948.
FLORES-MORAN, E.; YANEZ-PAZMINO, W.; BARZOLA-MONTESES, J. Genetic algorithm and fuzzy self-tuning PID for DC motor position controllers. In: 2018 19th International Carpathian Control Conference (ICCC). Hungary: IEEE, 2018.
GEE, W.; JAMES, F. A. J. L. Sturgeon, William (1783–1850). Oxford University Press, 2004. Disponível em: <https://www.oxforddnb.com/view/10.1093/ref:odnb/9780198614128.001.0001/odnb-9780198614128-e-26748>.
GHANY, M. A.; SHAMSELDIN, M. A.; GHANY, A. A. A novel fuzzy self tuning technique of single neuron PID controller for brushless DC motor. In: 2017 Nineteenth International Middle East Power Systems Conference (MEPCON). Nasr City, Egypt: IEEE, 2017.
GVR. Electric DC Motors Market Size, Share, Global Industry Report, 2025. United States: Grand View Research, 2017. 160 p.
HEKIMOGLU, B. Optimal tuning of fractional order PID controller for DC motor speed control via chaotic atom search optimization algorithm. IEEE Access, Institute of Electrical and Electronics Engineers (IEEE), v. 7, p. 38100–38114, 2019.
HORLA, D.; SADALLA, T. Optimal tuning of fractional-order controllers based on fibonacci-search method. ISA Transactions, Elsevier BV, v. 104, p. 287–298, Sep. 2020.
KOUASSI, B. A.; ZHANG, Y.; OUATTARA, S.; KIKI, M. J. M. PID tuning of chopper fed speed control of DC motor based on ant colony optimization algorithm. In: 2019 IEEE 3rd International Electrical and Energy Conference (CIEEC). Beijing, China: IEEE, 2019.
MIRJALILI, S. SCA: A sine cosine algorithm for solving optimization problems. Knowledge-Based Systems, Elsevier BV, v. 96, p. 120–133, mar 2016.
MIRJALILI, S.; MIRJALILI, S. M.; LEWIS, A. Grey wolf optimizer. Advances in Engineering Software, Elsevier BV, v. 69, p. 46–61, mar 2014.
RAMYA, M. A.; JADHAV, S. P.; PAWAR, S. N. Design and implementation of particle swarm optimization (PSO) tuned PID controller for speed control of permanent magnet brush less DC (PMBLDC) motor. In: 2020 International Conference for Emerging Technology (INCET). India: IEEE, 2020.
RAO, S. S. Engineering optimization: theory and practice. 4. ed. New Jersey: John Wiley & Sons, 2009. 813 p. ISBN 978-0-470-18352-6.
THAKUR, A.; MONGA, H.; SINGH, V. P.; KUMAR, R.; MATHUR, A. Sine cosine algorithm assisted tuning of PID controller for DC servo-motor. In: 2020 International Conference on Computation, Automation and Knowledge Management (ICCAKM). Dubai, United Arab Emirates: IEEE, 2020.
Downloads
Published
How to Cite
Issue
Section
License
Authors publishing in the Journal of Mechatronics Engineering agree to the following terms: Authors retain copyright and grant the journal the right of first publication, with the work licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License (CC BY - NC-SA 4.0). Our articles are available free and free, with privileges for educational, fishing and non-commercial activities.
