CLC number: TM33
On-line Access: 2024-08-27
Received: 2023-10-17
Revision Accepted: 2024-05-08
Crosschecked: 2010-12-10
Cited: 0
Clicked: 7632
Mounir Hadef, Mohamed-Rachid Mekideche. Moments and Pasek’s methods for parameter identification of a DC motor[J]. Journal of Zhejiang University Science C, 2011, 12(2): 124-131.
@article{title="Moments and Pasek’s methods for parameter identification of a DC motor",
author="Mounir Hadef, Mohamed-Rachid Mekideche",
journal="Journal of Zhejiang University Science C",
volume="12",
number="2",
pages="124-131",
year="2011",
publisher="Zhejiang University Press & Springer",
doi="10.1631/jzus.C0910795"
}
%0 Journal Article
%T Moments and Pasek’s methods for parameter identification of a DC motor
%A Mounir Hadef
%A Mohamed-Rachid Mekideche
%J Journal of Zhejiang University SCIENCE C
%V 12
%N 2
%P 124-131
%@ 1869-1951
%D 2011
%I Zhejiang University Press & Springer
%DOI 10.1631/jzus.C0910795
TY - JOUR
T1 - Moments and Pasek’s methods for parameter identification of a DC motor
A1 - Mounir Hadef
A1 - Mohamed-Rachid Mekideche
J0 - Journal of Zhejiang University Science C
VL - 12
IS - 2
SP - 124
EP - 131
%@ 1869-1951
Y1 - 2011
PB - Zhejiang University Press & Springer
ER -
DOI - 10.1631/jzus.C0910795
Abstract: Time moments have been introduced in automatic control because of the analogy between the impulse response of a linear system and a probability function. Pasek described a testing procedure for determining the DC parameters from the current response to a step in the armature voltage motor. In this paper, two identification algorithms developed based on the moments and pasek’;s methods are introduced and applied to the parameter identification of a DC motor. The simulation and experimental results are presented and compared, showing that the moments method makes the model closer to reality, especially in a transient regime.
[1]Basilio, J.C., Moreira, M.V., 2004. State-space parameter identification in a second control laboratory. IEEE Trans. Educat., 47(2):204-210.
[2]Bentayeb, A., Maamri, N., Trigeassou, J.C., 2007. The moments in control: a tool for analysis, reduction and design. Int. J. Comput. Commun. Control, 2(1):17-25.
[3]Burridge, M.J., Qu, Z., 2003. An improved nonlinear control design for series dc motors. Comput. Electr. Eng., 29(2):273-288.
[4]Chiasson, J., Bodson, M., 1993. Nonlinear control of shunt dc motor. IEEE Trans. Automat. Control, 38(11):1662-1666.
[5]Coirault, P., Trigeassou, J.C., Gaubert, J.P., Champenois, G., 1995. Parameter Estimation of an Induction Machine Using Reinitialized Partial Moment. IEEE Proc. Int. Conf. on Control Applications, p.979-984.
[6]Etien, E., Gabano, J.D., Rambault, L., Trigeassou, J.C., Mehdi, D., 2000. Frequential Moments: Application to Controller Reduction. IEEE Proc. American Control Conf., p.2869-2873.
[7]Goknar, I.C., Kutuk, H., Kang, S.M., 2001. MOMCO: method of moment components for passive model order reduction of RLCG interconnects. IEEE Trans. Circ. Syst. I: Fundam. Theory Appl., 48(4):459-474.
[8]Hadef, M., Bourouina, A., Mekideche, M.R., 2008. Parameter identification of a dc motor via moments method. Iran. J. Electr. Comput. Eng., 7(2):159-163.
[9]Jung, Y.G., Cho, K.Y., Lim, Y.C., Park, J.K., Chang, Y.H., 1992. Time-Domain Identification of Brushless DC Motor Parameters. Proc. IEEE Int. Symp. on Industrial Electronics, 2:593-597.
[10]Kara, T., Eker, I., 2004. Nonlinear modeling and identification of a dc motor for bidirectional operation with real time experiments. Energy Conv. Manag., 45(7-8):1087-1106.
[11]Louis, J.P., Multon, B., Lavabre, M., 1998. Commande des Machines à Courant Continu à Vitesse Variable. Traité de Génie Electrique, D3610-3611, Techniques de l’ Ingénieur (in French).
[12]Pasek, E., 1962. Novy zpusob urcent zakaladnich dynamickych parametru stejnosmernero motoru. Elektrotech. Obz., 51:109-114 (in Czech).
[13]Rigatos, G.G., 2009. Adaptive fuzzy control of dc motors using state and output feedback. Electr. Power Syst. Res., 79(11):1579-1592.
[14]Rubaai, A., Kotaru, R., 2000. Online identification and control of a dc motor using learning adaptation of neural networks. IEEE Trans. Ind. Appl., 36(3):935-942.
[15]Touhami, O., Guesbaoui, H., Iung, C., 1994. Asynchronous Machine Parameter Identification Using the Recursive Least-Squares Method. Proc. ICEM, p.458-462.
[16]Weerasooriya, S., El-Sharkawi, M.A., 1991. Identification and control of a DC motor using back propagation neural networks. IEEE Trans. Energy Conv., 6(4):663-669.
Open peer comments: Debate/Discuss/Question/Opinion
<1>