Journals / Balkan Journal of Electrical and Computer Engineering / 2016 / Cilt: 4 Sayı: 2

Implementation of Model Reference Adaptive Controller with Fractional Order Adjustment Rules for Coaxial Rotor Control Test System

Pages
84–88
Publication Date
2016-09-30
DOI
—
🏛️Bibliographic metadata and full text access for this article are provided via DergiPark.
DergiPark Record ↗
✨

AI Summary & Key Takeaways

AI Insight
⚡ TL;DR(Too Long; Didn't Read)

This experimental study is useful to show the utilization of fractional order control systems on engineering applications by using low-cost hardware.

📌 3 Key Takeaways

🎯
Objective & Hypothesis:In this study, an experimental test platform of a low-cost coaxial rotors has been developed for implementation of Model Reference Adaptive Controller (MRAC) with Fractional Order Adjustment Rules by using MATLAB/Simulink.
📊
Key Findings & Data:Setup of the test platform is presented and its performance is evaluated with real-time experimental measurements.
💡
Conclusion & Impact:This experimental study is useful to show the utilization of fractional order control systems on engineering applications by using low-cost hardware.
🔬Design:Modeling & Simulation
📍Scope:Comprehensive Sample
⚙️Variables:Adaptive PID controller · DC rotor control · fractional order integrator

Abstract

In this study, an experimental test platform of a low-cost coaxial rotors has been developed for implementation of Model Reference Adaptive Controller (MRAC) with Fractional Order Adjustment Rules by using MATLAB/Simulink. This paper provides a design method of MRAC with fractional order adjustment rule (FOAR-MRAC) that is implemented on a hardware based on ARM microcontroller. Setup of the test platform is presented and its performance is evaluated with real-time experimental measurements. This experimental study is useful to show the utilization of fractional order control systems on engineering applications by using low-cost hardware.

🔖

Cite This Article

Kavuran, G., Alagoz, B. B., Ates, A., Yeroglu, C. (2016). Implementation of Model Reference Adaptive Controller with Fractional Order Adjustment Rules for Coaxial Rotor Control Test System. Balkan Journal of Electrical and Computer Engineering, Cilt: 4 Sayı: 2, 84–88. https://ajindex.com/articles/1373395

📄 Full Text PDF Viewer

📄

PDF görüntüleyici hazırlanıyor...

References (21)

  1. J.G. Leishman, Principles of Helicopter Aerodynamics, Cambridge University Press, p. 8, 2006
  2. P.V. Osburn, H.P. Whitaker, A. Kezer, Comparative studies of systems, Institute of Aeronautical Science, pp. 61–39, 1961
  3. I.D. Landau, Adaptive Control the Model Reference Approach, Marcel Dekker: NY, USA, 1979
  4. K.J. Astrom, B. Wittenmark, Adaptive Control, Addison-Wesley, Reading, MA, USA, 1995
  5. B.M. Vinagre, I. Petrás, I. Podlubny, Y.Q. Chen, “Using fractional order adjustment rules and fractional order reference models in model-reference adaptive control”, Nonlinear Dynamics, Vol.29, pp. 269-279. 2001
  6. M.D. Bernardo, U. Montanaro, J.M. Olm, S. Santini, “Model reference adaptive control of discrete time piecewise linear systems”, International Journal of Robust and Nonlinear Control, Vol.23, pp.709-730. 2013
  7. K.A. Mohideen, G. Saravanakumar, K. Valarmathi, D. Devaraj, T.K. Radhakrishnan, “Real-coded Genetic Algorithm for system identification and tuning of a modified Model Reference Adaptive Controller for a hybrid tank system”, Applied Mathematical Modeling, Vol.37, pp.3829-3847, 2013
  8. T.A.V. Ravi, C. Chakraborty, S. Maiti, Y. Hori, “A new model reference adaptive controller for four quadrant vector controlled induction motor drives”, IEEE Transactions on Industrial Electronics, Vol.59, pp.3757-3767, 2012
  9. L. Guo, L. Parsa, “Model Reference Adaptive Control of Five-P IPM Motors Based on Neural Network”, IEEE Transactions on Industrial Electronics, Vol.59, pp.1500 – 1508, 2012
  10. Y. Liu, Y. Jia, “Adaptive leader-following consensus control of multi-agent systems using model reference adaptive control approach”, IET Control Theory & Applications, Vol.6, pp.2002-2008, 2012
  11. Z. Peng, D. Wang, H. Zhang, G. Sun, H. Wang, “Distributed model reference adaptive control for cooperative tracking of uncertain dynamical multi-agent systems”, IET Control Theory & Applications, Vol.7, pp.1079-1087, 2013
  12. H. Wu, M. Deng, “Robust adaptive control scheme for uncertain non-linear model reference adaptive control systems with time-varying delays”, IET Control Theory & Applications, Vol.9, pp.1181-1189, 2015
  13. B. Jiang, Z. Gao, P. Shi, Y. Xu, “Adaptive fault-tolerant tracking control of near-space vehicle using Takagi–Sugeno fuzzy models”, IEEE Transactions on Fuzzy Systems, Vol.18, pp.1000-1007, 2010
  14. I. Sadeghzadeh, A. Mehta, Y. Zhang, C.A. Rabbath, “Fault-tolerant trajectory tracking control of a quadrotor helicopter using gain-scheduled PID and model reference adaptive control”, Annual Conference of the Prognostics and Health Management Society, Montreal, Canada, pp. 1-10, 2011
  15. B.B. Alagoz, A. Ates, C. Yeroglu, “Auto-tuning of PID controller according to fractional-order reference model approximation for DC rotor control”, Mechatronics, Vol.23, pp.789–797, 2013
  16. I. Petras, Fractional-order nonlinear systems: modeling, analysis and simulation, Springer, Higher Education Press, Beijing, China, 2011
  17. C. Yeroglu, A. Ates, “A stochastic multi-parameters divergence method for online auto-tuning of fractional order PID controllers”, Journal of the Franklin Institute, Vol.351, pp.2411-2429, 2014
  18. C. Yeroglu, G. Kavuran, “Sliding mode controller design with fractional order differentiation: applications for unstable time delay systems”, Turkish Journal of Electrical Engineering & Computer Sciences, Vol.22, pp.1270-1286, 2014
  19. D. Sierociuk, I. Podlubny, I. Petras, “Experimental evidence of variable-order behavior of ladders and nested ladders”, Control Systems Technology, Vol.21, pp.459-466, 2013
  20. Y.Q. Chen, B.M. Vinagre, I. Podlubny, “Continued fraction expansion approaches to discretizing fractional order derivatives an expository review”, Nonlinear Dynamics, Vol.38, pp.155-170, 2004
  21. E. Lavretsky, Adaptive control: Introduction, overview, and applications, NASA Adaptive Control Workshop 2009, NASA Marshall Space Center, Huntsvill, USA, 2009.