1

EKF-Based PI-/PD-Like Fuzzy-Neural-Network Controller for Brushless Drives

Student : Tz-Han Jung

Rubaai, A.; Young, P. Industry Applications, IEEE Transactions onVolume: 47 , Issue: 6 Digital Object Identifier: 10.1109/TIA.2011.2168799Publication Year: 2011 , Page(s): 2391 – 2401IEEE JOURNALS & MAGAZINES

2

Abstract

This paper presents the development of a fuzzyneural-network (FNN) proportional–integral (PI)-/proportional–derivative (PD)-like controller with online learning for speed trajectory tracking of a brushless drive system. The design implements the novel use of the extended Kalman filter (EKF) to train FNN structures as part of the PI-/PD-like fuzzy design.

The objective is to replace the conventional PI–derivative (PID) controller with the proposed FNN PI-/PD-like controller with EKF learning mechanism.

3

Proposed PI-/PD-like FNN controller structure

4

5

FNN PI.PD structure

6

7

Block diagram of the hardware apparatus

8

under normal condition

9

under zero speed

10

under disturbance

11

under load

12

under constant speed

13

poor initial condition & training improvement

14

REFERENCES [1] A. Sant and K. R. Rajagopal, “PM synchronous motor speed control using hybrid fuzzy-PI with novel switching

functions,” IEEE Trans. Magn.,vol. 45, no. 10, pp. 4672–4675, Oct. 2009. [2] B. M. Hohan and A. Sinha, “Analytical structure and stability analysis of a fuzzy PID controller,” Appl. Soft

Comput., vol. 8, no. 1, pp. 749–758,Jan. 2008. [3] A. Rubaai, M. J. Castro-Sitiriche, and A. R. Ofoli, “DSP-based laboratory implementation of hybrid fuzzy-PID

controller using genetic optimization for high performance motor drives,” IEEE Trans. Ind. Appl., vol. 44, no. 6, pp. 1977–1986, Nov./Dec. 2008.

[4] Y.-P. Kuo and T.-H. S. Li, “GA-based Fuzzy PI/PD controller for automotive active suspension system,” IEEE Trans. Ind. Electron., vol. 46, no. 6, pp. 1051–1056, Dec. 1999.

[5] B.-G. Hu, G. K. I.Mann, and R. Gosine, “A systematic study of fuzzy PID controllers—Function-based evaluation approach,” IEEE Trans. Fuzzy Syst., vol. 9, no. 5, pp. 699–712, Oct. 2001.

[6] H.-X. Li, L. Zhang, K.-Y. Cai, and G. Chen, “An improved robust fuzzy-PID controller with optimal fuzzy reasoning,” IEEE Trans. Syst., Man,Cybern. B, Cybern., vol. 35, no. 6, pp. 1283–1294, Dec. 2005.

[7] M.Masiala, B. Vafakhah, J. Salmon, and A.M. Knight, “Fuzzy self-tuning speed control of an indirect field-oriented control induction motor drive,” IEEE Trans. Ind. Appl., vol. 44, no. 6, pp. 1732–1740, Nov./Dec. 2008.

[8] M. Barut, S. Bogosyan, and M. Gokasan, “Speed sensorless estimation for induction motors using extended Kalman filters,” IEEE Trans. Ind. Electron., vol. 54, no. 1, pp. 272–280, Feb. 2007.

[9] K. Szabat and T. Orlowska-Kowalska, “Performance improvement of industrial drives with mechanical elasticity using nonlinear adaptive Kalman filter,” IEEE Trans. Ind. Electron., vol. 55, no. 3, pp. 1075–1084, Mar. 2008.

[10] K. K. Ahn and D. Q. Truong, “Online tuning fuzzy PID controller using robust extended Kalman filter,” J. Process Control, vol. 19, no. 6, pp. 1011–1023, Jun. 2009.

[11] D. J. Lary and H. Y. Mussa, “Using an extended Kalman filter learning algorithm for feed-forward neural networks to describe tracer correlations,” Atmos. Chem. Phys. Discuss., vol. 4, pp. 3653–3657, 2004.

[12] S. Singhal and L. Wu, “Training feedforward networks with extended Kalman filter algorithm,” in Proc. Int. Conf. ASSP, 1989, pp. 1187–1190.

15

REFERENCES [13] S.-J. Ho, L.-S. Shu, and S.-Y. Ho, “Optimizing fuzzy neural networks for tuning PID controllers using an

orthogonal simulated annealing algorithm OSA,” IEEE Trans. Fuzzy Syst., vol. 14, no. 3, pp. 421–434, Jun. 2006. [14] I. del Campo, J. Echanobe, G. Bosque, and J. M. Tarela, “Efficient hardware/ software implementation of an

adaptive neuro–fuzzy system,” IEEE Trans. Fuzzy Syst., vol. 16, no. 3, pp. 761–778, Jun. 2008. [15] M. N. Uddin and M. A. Rahman, “Development and implementation of a hybrid intelligent controller for interior

permanent-magnet synchronous motor drives,” IEEE Trans. Ind. Appl., vol. 40, no. 1, pp. 68–76, Jan./Feb. 2004. [16] dSPACE User’s Guide, Digital Signal Processing and Control Engineering, dSPACE, Paderborn, Germany,

2003. [17] G413-817 Technical Data Manual, Moog Aerospace, East Aurora, New York, 2000. [18] T200-410 Technical Data Manual, Moog Aerospace, East Aurora, New York, 2000.

16

Thank you for your attention.

17

Q & A.