Using Feedback Error Learning for Control of Electro Hydraulic Servo System by Laguerre

Subject Areas : Renewable energy

Amir Reza Zare Bidaki ¹ (Instructor /Islamic Azad University, Boueen Zahra Branch)
Mojtaba Malboobi ² (Instructor /Instructor Islamic Azad University, Science & Research Branch, Tehran)
Seyyed Mohammad Kargar ³ (Instructor /Islamic Azad University, Najafabad Branch)
Mehdi Aliyari Shoreh Deli ⁴ (Assistant Professor /Khajeh Nasirodin Toosi University, Tehran)

Received: 2012-09-22 Accepted : 2013-12-06 Published : 2014-02-01

Keywords: Electro Hydraulic Servo System (EHSS), Feedback Error Learning (FEL), Laguerre Controller,

Abstract :

In this paper, a new Laguerre controller is proposed to control the electro hydraulic servo system. The proposed controller uses feedback error learning method and leads to significantly improve performance in terms of settling time and amplitude of control signal rather than other controllers. All derived results are validated by simulation of nonlinear mathematical model of the system. The simulation results show the advantages of the proposed method for improved control in terms of both settling time and amplitude of control signal.

References:

[1] H.E. Merritt, "Hydraulic control system", New York: John Wiley & Sons, Inc., 1967.

[2] J. Watton, "Fluid power system", New York: Prentice Hall, 1989.

[3] M.Jo., "Nonlinear control of an Electro Hydraulic Velocity Servo System", ACC, Anchorage, Alaska, USA, 2002.

[4] S.A.R. Mohseni, M. Aliyari Shooredeli, M. Teshnehlab, "EHSS velocity control by fuzzy neural networks", IEEE/NAFIPS, pp. 13-18, Meeting of the 2006.

[5] H. Azimian, R. Adlgostar, M.Teshnehlab, "Velocity control of an electro hydraulic servomotor by neural networks", IEEE/ICPC, Russia, Aug. 24-26, 2005.

[6] S.A.R. Mohseni, M. Aliyari Shooredeli, M. Teshnehlab, "Decoupled sliding-mode with fuzzy neural network controller for EHSS velocity control", IEEE/ICIAS, Malaysia, 2007.

[7] Ch.L. Asokanthan, "CMAC based controller for hydro mechanical systems", IEEE/ACC, Arlington, VA, SA, 2001.

[8] T. Oliveira e Silva, "Laguerre filters: An introduction", Revista do DETUA, Vol. 1, No. 3, pp. 237-248, Jan. 1995.

[9] H. Miyamoto, M. Kawato, T. Setoyama, R. Suzuki, "Feedback error learning neural network for trajectory control of a robotic manipulator", Neural Networks, Vol. 1, pp. 251-265, 1988.

[10] M. Kawato, "Computational schemes and neural network models for formation and control of multijoint arm trajectory", In W.T. Miller, R.S. Sutton, P.J. Werbos (Eds), Neural networks for control, The MIT Press, 1990.

[11] V.D. Kalanovic, D. Popovic, N.T.Skaug, "Feedback error learning neural netmoral 1989work for Trans-femoral prosthesis", IEEE Trans. on Rehab. Eng., Vol. 8, No.1, March 2000.

[12] M. Tavan, M. Aliyari Shooredeli, A.R. Zare Bidaki, "Stability of feedback error learning for linear systems", Milano, Italy, IFAC World Congress, 2011.

[13] M. Malboubi, F. Razzazi, M. Aliyari Shooredeli, "Elimination of power line noise from EMG signals using an efficient adaptive laguerre filter", IEEE/ICSES, 2010.

[14] H. Belt, "Orthonormal bases for adaptive filtering", PhD Thesis 2008 .

[15] M. Asadi, F. Razzazi, "Adaptive determination of the free parameters of generalized orthonormal IIR adaptive filters using genetic algorithm", IEEE/ICCCC, 2009.