Speed control of a magnetic accelerator using adaptive control techniques

Authors

  • Javier Blanco Rico Universidad Politécnica de Madrid https://orcid.org/0000-0002-0997-2821
  • Basil Mohammed Al-Hadithi Centre for Automation and Robotics, Universidad Politécnica de Madrid-CSIC https://orcid.org/0000-0002-8786-5511
  • Roberto Gonzalez Herranz School of Industrial Design and Engineering, Universidad Politécnica de Madrid

Keywords:

Adaptation models, Adaptive algorithms, Automatic control, Control engineering, Digital control, Negative feedback, Nonlinear dynamical systems, Output feedback, Programmable control, Regulators, Velocity control

Abstract

Advanced control algorithms are of great interest in control engineering, they make it possible to guarantee the correct operation of complex systems and improve their performance under adverse operating conditions, thanks to negative output feedback. In this work, two adaptive control algorithms are shown: controllers based on Gain Scheduling and Direct Self-Tuning Regulators, using them to control the velocity of an electromagnetic accelerator and comparing their results with those obtained by a classic PID regulator when the system is operated under adverse operating conditions (setpoint changes, load changes and noise resistance). lt shows how this type of regulators can exceed the performance of classical control algorithms, making them a very attractive alternative for digital systems based on microcontrollers, whose high processing capacity allows them to be easily implemented in a wide variety of processes, including nonlinear dynamical systems.

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Author Biographies

Javier Blanco Rico, Universidad Politécnica de Madrid

Javier Blanco Rico, Madrid, Spain. B. Se. in Industrial Electronics and Automation Engineering from the Universidad Politécnica de Madrid (UPM) (Spain) in 2021. He is now carrying out master's studies in the field of power electronics and embedded systems at the Universidad Politécnica de Madrid.

Basil Mohammed Al-Hadithi, Centre for Automation and Robotics, Universidad Politécnica de Madrid-CSIC

Basil Mohammed Al-Hadithi got the title of B. Sc. in control and system engineering in 1983 and the M. Sc. in control and instrumentation engineering in 1988. He received a PhD in process control and artificial intelligence in 2002 from Universidad Politécnica de Madrid (UPM) (Spain) with a thesis on analysis, design and stability of fuzzy slide-mode control systems. He is an associate professor at UPM. His teaching activity covers control engineering and analogue electronics, being an author and co-author of seven textbooks and having supervised and co-supervised several B. Sc. final year projects and M. Sc. theses and 4 theses. He is a researcher at the Centre for Automation and Robotics UPM-CSIC. His interest is mainly focused on fuzzy control and slide mode control. He has several publications (JCR), book chapters and conference papers. Moreover, he has participated in several research projects and industrial contracts with companies. He is a board member and reviewer of several international scientific societies and International journals in modelling and designing control systems.

Roberto Gonzalez Herranz, School of Industrial Design and Engineering, Universidad Politécnica de Madrid

Roberto Gonzalez Herranz finished his B. Se. in Electrical Engineering in 1992, and M. Se. in Industrial Engineer in 1996. He is an associate professor at UPM at the Universidad Politécnica de Madrid (UPM) since 2001. He obtained his PhD title in Robotics and Computer Vision in 2016 from the Center of Automation and Robotics (CAR), formed by UPM y CSIC (Spain). He is a researcher at the Centre for Automation and Robotics UPM-CSIC. His academic and research activity is focused on Automation and Control. He supervised and co-supervised various B. Se. final year projects and M. Se theses. He has several publications in scientific journals and conferences.

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Published

2021-10-19

How to Cite

Blanco Rico, J., Al-Hadithi, B. M., & Gonzalez Herranz, R. (2021). Speed control of a magnetic accelerator using adaptive control techniques. IEEE Latin America Transactions, 20(3), 488–495. Retrieved from https://latamt.ieeer9.org/index.php/transactions/article/view/5936

Issue

Vol. 20 No. 3 (2022): Ordinary Issue

Section

Articles