Analysis of the Nonrecursive Advanced Optimal Control of the Permanent Magnet Synchronous Motor Drive

Abstract:

The paper aims to underline the importance of applying complete optimal control to electric drives, in particular to Permanent Magnet Synchronous Motor (PMSM). The proposed optimal control has three components: the feedback componentassures energy minimization; the forcing component assures the zero steady state; the feedforward compensating component assures fast compensation of the disturbance. The methodology of obtaining this type of the advanced optimal control is based on variational calculus. The solution is a nonrecursive one, avoiding memorizing it from the final time to the initial time, as in the recursive case. Moreover, the solution is orientated to numerical implementation by using a zero order hold in order to solve adequately the matrix Riccati differential equation (MRDE). The practical implication of using the proposed method is the on-line computing possibility of the optimal control solution. The influences of the control weighted matrix upon the manipulated variable of the PMSM electric drive are shown by numerical simulation.

• Periodical: Applied Mechanics and Materials (Volume 367)
• Pages: 194-198
• DOI: https://doi.org/10.4028/www.scientific.net/AMM.367.194
• Online since: August 2013
• Authors: Marian Gaiceanu, Emil Rosu
• Keywords: Isotropic, MATLAB, Matrix Riccati Differential Equation, Optimal Control, Permanent Magnet Synchronous Machine

References

[1] M. Veerachary: Optimal control strategy for a current source inverter fed induction motor, Computers and Electrical Engineering, Vol. 28, No. 4, July (2002), pp.255-267.

DOI: 10.1016/s0045-7906(00)00051-3

[2] J.M. Kh. Tamimiand H.M. Jaddu: Optimal vector control of three-phase induction machine, International Association of Science and Technology for Development, Proceedings of the 25th IASTED International Conference on Modeling, Identification and Control, Lanzarote, Spain, Acta Press, CA USA, ISSN 0-88986-549-3, (2006).

[3] T. Cheng, F.L. Lewis and M. Abu-Khalaf: A neural network solution for fixed-final time optimal control of nonlinear systems, Automatica, Journal of IFAC, Vol. 43, Pergamon Press, Inc., March (2007), pp.482-490.

DOI: 10.1016/j.automatica.2006.09.021

[4] C.T. Su and C.L. Chiang: Optimal Position/Speed Control of Induction Motor Using Improved Genetic Algorithm and Fuzzy Phase Plane Controller, Journal of Control and Intelligent Systems, ISSN 1480-1752, Vol. 32, (2004).

DOI: 10.2316/journal.201.2004.2.201-1315

[5] M. Matinfar and K. Hashtrudi-Zaad: Optimization-based Robot Compliance Control: Geometric and Linear Quadratic Approaches, International Journal of Robotics Research, ISSN 0278-3649, Sage Publications, Inc., Vol. 24, pp.645-656, August (2005).

DOI: 10.1177/0278364905056347

[6] V.S. Deneika: Optimal control of the dynamic state of a thin compound plate, Journal of Cybernetics and Systems Analysis, Vol. 42, Kluwer Academic Publishers, ISSN 1060-0396, (2006), pp.587-608.

DOI: 10.1007/s10559-006-0096-1

[7] S. Zhongke: Optimal fuzzy control for nonlinear system and application to AC motor control, Power Electronics and Motion Control Conference, 2004, IPEMC 2004, The 4th International, Vol. 3, 14-16Aug. (2004), pp.1331-1334.

[8] L. Jianqiang, Yang, L., F., Z. Zheng and Q. Trillion: Optimal Efficiency Control of Linear Induction Motor Drive for Linear Metro, 2nd IEEE Conference on Industrial Applications, 2007, ICIEA 2007, 23-25 May 2007, pp.1981-1985, ISBN 978-1-4244-0737-8 (2007).

DOI: 10.1109/iciea.2007.4318756

[9] M. Athans and P. L. Falb: Optimal Control, Mc Graw-Hill, New York (1966).

[10] W. Leonhard: Control of Electrical Drives, Springer-Verlag, Berlin (1996).

[11] E. Rosu, M. Gaiceanu and I. Bivol: Optimal Control Strategy for AC Drives. IEEE- PEMC '98, 8th International Power Electronics & Motion Control Conference, Prague, Czech Republic, 4. 160-4. 165 (1998).