Abstract : Control of Induction Motor (IM) is well known to be
difficult owing to the fact the models of IM are highly nonlinear
and time variant. In this paper, to achieve accurate control
performance of rotor position control of IM, a new method is
proposed by using adaptive inverse control (AIC) technique. In
recent years, AIC is a very vivid field because of its advantages.
It is quite different from the traditional control. AIC is actually
an open loop control scheme and so in the AIC the instability
problem cased by feedback control is avoided and the better
dynamic performances can also be achieved. The model of IM is
identified using adaptive filter as well as the inverse model of the
IM, which was used as a controller. The significant of using the
inverse of the IM dynamic as a controller is to makes the IM
output response to converge to the reference input signal. To
validate the performances of the proposed new control scheme,
we provided a series of simulation results.
Aamir Hashim Obeid Ahmed
Martino O. Ajangnay
Shamboul A. Mohamed
Matthew W. Dunnigan
Bose, B.K., ‘Modern power electronics and ac drives’, Pearson education, Inc., Indian, 2002
S.Wade, M.W.Dunnigan, B.W.Williams, X.Yu, ‘Position control of a vector controlled induction machine using slotine’s sliding mode control’, IEE Proceeding Electronics Power Application, Vol. 145, No.3, pp.231-238, 1998.
S.J.Chapman, ‘Electric Machinery Fundamentals’, The McGraw-Hill Companies,
Z.Beres, P.Vranka, ‘Sensorless IFOC of induction motor with current regulators in current reference frame’, IEEE Transactions on Industry Applications, Vol.37, pp.1012-1018, July 2001
F. Blaschke, ‘The Principle of Field Orientation as Applied to the new Transvektor Closed-Loop Control System for Rotating Machines’, Siemens Review, No. 34, 1972, pp217-220.
R.J.Wai, K.H.Su, C.Y.Tu, ‘Implementation of adaptive enhanced fuzzy sliding mode control for indirect field oriented induction motor drive’, IEEE International Conference on Fuzzy Systems, pp.1440-1445, 2003.
 P.Vas, ‘Vector control of ac machines’, Oxford University Press, 1990.
Trzynadlowski, ‘The field oriented principle control of induction motors’, Kluwer academic publishers, Massachusetts 02061 USA, 1994, pp813-818.
B.Widrow, E.Walach, ‘Adaptive Inverse Control’, Prentice Hall Inc., NJ. 1996
B.Widrow, S.D.Stearns, ‘Adaptive signal processing’, Prentice-Hall, Englewood Cliffs, New Jersey, 1985.
G.L.Plett, ‘Adaptive inverse control of linear and nonlinear system using dynamic neural networks’, IEEE Transactions on neural network, Vol.14, No.2, March 2003.
S.Haykin, ‘Adaptive filter theory’, 4 th ed. Englewood Cliffs, New Jersey Prentice Hall, 2001.
J.Kim, E.T.Perry, ‘Performance analysis of the self correcting adaptive filters’, IEEE, pp.316-319, 2005.
M.H.Hayes, ‘Statistical digital signal processing and modelling’, Jon Wiley and Sons, 1996.
R.R.Bitmead, B.D.O.Anderson, ‘Performance of adaptive estimation algorithms in dependent random environments’, IEEE Trans. On Automation Control, Vol. AC-25, pp.788-794, 1980.
Y.Ahmed, F.Jawed, S.Zia, M.S.Aga, ‘Real time implementation of adaptive channel equalization algorithms on TMS320C6x DSP processors’, IEEE, 2004.
All Right Reserved for Sudan University of Science and Technology - 2016