Adaptive diffuse control for a non-linear helicopter mechanism

Article Sidebar

PDF (Spanish)
Published: 2013-12-30
DOI: https://doi.org/10.17163/ings.n10.2013.01
Keywords:
Fuzzy model reference learning control (FMRLC), fuzzy controller, member functions, proportional derivative (PD), steady-state error.

Main Article Content

Juan Paúl Ortiz González

Abstract

This paper presents the analyze the adaptive Fuzzy Model Reference Learning Control (FMRLC) is a adaptive fuzzy control method used in nonlinear plants, time-varying and difficult to model them mathematically, which provides a methodology to adapt to the error that occurs with the actual plant and the reference model, the performance is obtained when the error tends to be very small, this adaptation is achieved by moving the centers of the member functions of the knowledge base of fuzzy controller, according to an adaptation algorithm. The fuzzy controller is proposed to solve the control problem is a fuzzy proportional derivative controller (PD). The elimination of steady-state error is thanks to an integral gain FMRLC parallel to the controller.

Article Details

Issue
No. 10 (2013): July / December
Section
Scientific Paper

 

The Universidad Politécnica Salesiana of Ecuador preserves the copyrights of the published works and will favor the reuse of the works. The works are published in the electronic edition of the journal under a Creative Commons Attribution/Noncommercial-No Derivative Works 4.0 Ecuador license: they can be copied, used, disseminated, transmitted and publicly displayed.

The undersigned author partially transfers the copyrights of this work to the Universidad Politécnica Salesiana of Ecuador for printed editions.

It is also stated that they have respected the ethical principles of research and are free from any conflict of interest. The author(s) certify that this work has not been published, nor is it under consideration for publication in any other journal or editorial work.

The author (s) are responsible for their content and have contributed to the conception, design and completion of the work, analysis and interpretation of data, and to have participated in the writing of the text and its revisions, as well as in the approval of the version which is finally referred to as an attachment.

Author Biography

Juan Paúl Ortiz González

Ingeniero electrónico, Egresado de la Maestría en Control y Automatización Industrial, Universidad Politécnica Salesiana, sede Cuenca

References

J. Layne and K. Passino, “Fuzzy model reference learning control for cargo ship steering,” Control Systems, IEEE, vol. 13, no. 6, pp. 23–34, 1993.

J. Layne, “Fuzzy model learning control,” Master’s thesis, Department of Electrical Engineering, The Ohio State University, March 1992.

K. Passino and S. Yurkovich, Fuzzy Control, 1st ed. United States: Addison-Wesley, 1997.

R. C. Dorf, Modern control systems. AddisonWesley Longman Publishing Co., Inc., 1991.

P. Antsaklis and K. Passino, An Introduction to Intelligent and Autonomous Control. Kluwer Academic Publishers, 1993.

J. R. Layne, K. M. Passino, and S. Yurkovich, “Fuzzy learning control for antiskid braking systems,” Control Systems Technology, IEEE Trans-
actions on, vol. 1, no. 2, pp. 122–129, 1993.

K. Tanaka and H. O. Wang, Fuzzy control systems design and analysis: a linear matrix inequality approach. Wiley. com, 2004.
N. Abdellatif, Y. Ramdani, and H. Hamdaoui, “A new adaptive controller of facts-based fmrlc aimed at improving power system stability,” Serbian Journal of Electrical Engineering, vol. 5, no. 2, pp. 229–245, 2008.

B. Kuo and F. Golnaraghi, Automatic control systems. John Wiley & Sons New York, 2003, vol. 4.

K. Ogata, Ingeniería de control moderna 4ED. Pearson Educación, 2003.

G. J. Klir and B. Yuan, Fuzzy sets and fuzzy logic. Englewood Cliffs, New Jersey: Prentice Hall, 1995.

H. J. Zimmermann, Fuzzy set theory-and its applications, 2nd ed. Springer, 2001.

T. Mathworks, “Fuzzy logic toolbox for use with Matlab,” 2006.

P. Khundia and D. Mitra, “Fuzzy model reference learning controller for pitch control system of an aircraft,” Georgia Electronic Scientific Journal, no. 3, 2009.