Please wait a minute...
Shopping Cart Email List Chinese
Advanced Search Fig/Tab
Frontiers of Electrical and Electronic Engineering

ISSN 2095-2732

ISSN 2095-2740(Online)

CN 10-1028/TM

Featured Articles  |  Most Downloaded  |  Most Reading
Online Submission Subscribe to Our RSS Content Feed
Front Elect Electr Eng    2012, Vol. 7 Issue (3) : 337-346    https://doi.org/10.1007/s11460-012-0204-0
RESEARCH ARTICLE
H-infinity robust control technique for controlling the speed of switched reluctance motor
A. RAJENDRAN(), S. PADMA
Department of Electrical and Electronics Engineering, Sona College of Technology, Salem, Tamilnadu, India
 Download: PDF(511 KB)   HTML
 Export: BibTeX | EndNote | Reference Manager | ProCite | RefWorks
Abstract

The switched reluctance motor (SRM) is applied in various industrial applications due to its profitable advantages. However, the robustness speed of SRM is one of the major drawbacks, which greatly affects the performance of motor. Thus, the aim of this paper is to control the speed of SRM using H-infinity control strategy. This H-infinity control technique is stronger against robustness. In the proposed speed controller, the rotor position of the SRM is applied to the controller. The speed variation of the rotor is determined from the reference speed and applied to the controller as input. Then, the speed variation and the corresponding sensitivity function are determined. The sensitivity function determination is based on the input weight of the controller. The weight adjustment process is repeated until a stable speed condition is achieved. Then, the output of the proposed control technique is compared with the existing control technique and the robustness is analyzed. Here, the existing control techniques considered are proportional-integral (PI) controller and fuzzy logic controller (FLC)-based PI gain tuning. The proposed control strategy is simulated in MATLAB working platform and the control performance is analyzed.
Keywords switched reluctance motor (SRM)      speed control technique      H-infinity control      robust     
Corresponding Author(s): RAJENDRAN A.,Email:arajendranphd@gmail.com   
Issue Date: 05 September 2012
 Cite this article:   
A. RAJENDRAN,S. PADMA. H-infinity robust control technique for controlling the speed of switched reluctance motor[J]. Front Elect Electr Eng, 2012, 7(3): 337-346.
 URL:  
https://academic.hep.com.cn/fee/EN/10.1007/s11460-012-0204-0
https://academic.hep.com.cn/fee/EN/Y2012/V7/I3/337
Fig.1  (a) Cross section and (b) equivalent circuit of 6/4-pole SRM
Fig.2  Proposed SRM drive system
Fig.3  -infinity feedback control structure configuration
Fig.4  Simulink model of the proposed control system
Fig.5  Simulink model of -infinity controller
Fig.6  Performance of SRM rotor speed
Fig.7  Performance of SRM torque
Fig.8  Performance of rotor flux
Fig.9  Performance of motor output voltage
Fig.10  Performance of motor output current
Fig.11  Performance of SRM transfer function model
Fig.12  Discrete PI controller based SRM control model
Fig.13  Mamdani fuzzy controller based SRM control model
Fig.14  Performance of rotor speed without speed controller
Fig.15  Rotor speed comparison of -infinity control and without control
Fig.16  Rotor speed comparison of -infinity control and PI control
Fig.17  Rotor speed comparison of -infinity control and fuzzy control
Fig.18  Performance of speed control action in time
1 Sedghizadeh S, Lucas C, Ghafoori Fard H. Sensorless speed control of switched reluctance motor drive using the binary observer with online flux-linkage estimation. Iranian Journal of Electrical & Electronic Engineering , 2009, 5(2): 143-150
2 Rares T, Virgil C, Lorand S, Calin M. Artificial intelligence based electronic control of switched reluctance motors. Journal of Computer Science and Control Systems , 2011, 4(1): 193-198
3 Daldaban F, Ustkoyuncu N. Inductance estimating of linear switched reluctance motors with the use of adaptive neuro-fuzzy inference systems. Journal of Science , 2009, 22(2): 89-96
4 Hashem G M, Hasanien H M. Speed control of switched reluctance motor based on fuzzy logic controller. In: Proceedings of the 14th International Middle East Power Systems Conference . 2010, 288-292
5 Nagel N J, Lorenz R D. Modeling of a saturated switched reluctance motor using an operating point analysis and the unsaturated torque equation. In: Proceedings of the 1999 IEEE Industry Applications Conference . 1999, 4: 2219-2226
6 Tsai M C, Huang C C, Huang Z Y. A new two-phase homopolar switched reluctance motor for electric vehicle applications. Journal of Magnetism and Magnetic Materials , 2003, 267(2): 173-181
doi: 10.1016/S0304-8853(03)00350-0
7 Yoon Y H, Kim Y C, Song S H, Won C Y. Control of c-dump converters fed from switched reluctance motors on an automotive application. Journal of Power Electronics , 2005, 5(2): 120-128
8 8.Vijayan S, Paramasivam S, Arumugam R, Vasudevan M, Palaniswami S. An intelligent self-tuning PI type fuzzy logic controller for a switched reluctance motor drive. Iranian Journal of Electrical and Computer Engineering , 2007, 6(2): 87-97
9 Rodrigues M, Costa Branco P J, Suemitsu W. Fuzzy logic torque ripple reduction by turn-off angle compensation for switched reluctance motors. IEEE Transactions on Industrial Electronics , 2001, 48(3): 711-715
doi: 10.1109/41.925598
10 Gupta R A,Bishnoi S K,Kumar R. Sensorless control of switched reluctance motor drive with fuzzy logic based rotor position estimation. International Journal of Computer Applications , 2010, 1(22): 72-79
11 11.Tandon P, Velayutham Rajarathnam A, Ehsani M. Self-tuning control of a switched-reluctance motor drive with shaft position sensor. IEEE Transactions on Industry Applications , 1997, 33(4): 1002-1010
doi: 10.1109/28.605742
12 Wadnerkar V S, TulasiRam Das G, Rajkumar A D. Performance analysis of switched reluctance motor; design, modeling and simulation of 8/6 switched reluctance motor. Journal of Theoretical and Applied Information Technology , 2008, 4(11): 1118-1124
13 Hwu K I. Applying POWERSYS and SIMULINK to modeling switched reluctance motor. Tamkang Journal of Science and Engineering , 2009, 12(4): 429-438
14 Felix Joseph X, Pushpa Kumar S. Design and simulation of a PI controlled soft switched front end converter for switched reluctance motor. International Journal of Computer Applications , 2011, 34(10): 9-15
15 Lin W M, Hong C M, Chen C H, Chien H C. Implementation of a DSP-based hybrid sensor for switched reluctance motor converter. International Journal of Energy and Environment , 2010, 1(5): 841-860
16 Rafiq M. Saeed-ur-Rehman, Fazal-ur-Rehman, Raza Q. Power efficient higher order sliding mode control of SR motor for speed control applications. International Journal of Computer Science Issues , 2011, 8(1): 378-387
17 Alarcin F. Internal model control using neural network for ship roll stabilization. Journal of Marine Science and Technology , 2007, 15(2): 141-147
18 Nair S S. Automatic weight selection algorithm for designing H infinity controller for active magnetic bearing. International Journal of Engineering Science and Technology , 2011, 3(1): 122-138
19 Alcantara S, Skogestad S, Grimholt C, Pedret C, Vilanova R. Tuning PI controllers based on H-infinity weighted sensitivity. In: Proceedings of the 19th Mediterranean Conference on Control and Automation . 2011, 1301-1306
20 Salami A, Feizi M. Analysis of H-infinity controllers in fuel cell powered uninterruptible power supply system. World Academy of Science, Engineering and Technology , 2011, 73: 137-140
21 Karakas E, Vardarbasi S. Speed control of SR motor by self-tuning fuzzy PI controller with artificial neural network. Sadhana , 2007, 32(5): 587-596
doi: 10.1007/s12046-007-0044-4
22 Tahour A, Abid H, Aissaoui A G. Adaptive neuro-fuzzy controller of switched reluctance motor. Serbian Journal of Electrical Engineering , 2007, 4(1): 23-34
doi: 10.2298/SJEE0701023T
23 Tahour A, Meroufel A, Abid H, Aissaoui A G. Sliding controller of switched reluctance motor. Leonardo Electronic Journal of Practices and Technologies , 2008, (12): 151-162
24 Kamala Kannan C, Paranjothi S R, Paramasivam S. Optimal control of switched reluctance motor using tuned fuzzy logic control. European Journal of Scientific Research , 2011, 55(3): 436-443
25 Srivastava K,Singh B K, Arya K V, Singh R K. Simulation and modeling of 8/6 switched reluctance motor using digital controller. International Journal of Electronics Engineering , 2011, 3(2): 241-246
26 Rafiq M, Saeed-ur-Rehman, Fazal-ur-Rehman, Butt Q R. Performance comparison of PI and sliding mode for speed control applications of SR motor. European Journal of Scientific Research , 2011, 50(3): 363-380
27 Wang S C, Liu Y H, Lee C C. A modified PI-like fuzzy logic controller for switched reluctance motor drive. IEEE Transactions on Industrial Electronics , 2011, 58(5): 1812-1825
doi: 10.1109/TIE.2010.2058074
28 Filardi G, Sename O, Besancon-Voda A, Schroeder H J. Robust H∞ control of a DVD drive under parametric uncertainties. In: Proceedings of European Control Conference . 2003, 1-6
[1] Yanhong LIU, Jianyong LI, Chunwen LI. Robust excitation control of multi-machine multi-load power systems using Hamiltonian function method[J]. Front Elect Electr Eng Chin, 2011, 6(4): 547-555.
[2] Lijun ZHANG, Zhengguang CHEN, Miao ZHENG, Xiaofei HE. Robust non-negative matrix factorization[J]. Front Elect Electr Eng Chin, 2011, 6(2): 192-200.
[3] Haiyun AN, Hongjie JIA, Yuan ZENG, Wei WEI, . Equivalence of stability criteria for time-delay systems[J]. Front. Electr. Electron. Eng., 2010, 5(2): 207-217.
[4] Jianbin QIU, Gang FENG, Jie YANG, . New approaches to delay-dependent robust H ∞ control of uncertain discrete-time T-S fuzzy systems with time-varying delay[J]. Front. Electr. Electron. Eng., 2009, 4(4): 378-391.
[5] Ying YANG, Junmin LI, Ying YANG, Xiaofen LIU. Analysis of stability and robust stability for stochastic hybrid systems with impulsive effects[J]. Front Elect Electr Eng Chin, 2009, 4(1): 66-71.
[6] XIANG Zhengrong, XIANG Weiming. Design of controllers for a class of switched nonlinear systems based on backstepping method[J]. Front. Electr. Electron. Eng., 2008, 3(4): 465-469.
[7] SONG Xin, WANG Jinkuan, HAN Yinghua, WANG Han. Robust adaptive beamforming algorithm based on Bayesian approach[J]. Front. Electr. Electron. Eng., 2008, 3(4): 435-439.
[8] GU Danying, YANG Jiwen, ZHANG Weidong. Analytical design of PI controller for AQM with robustness adjustability[J]. Front. Electr. Electron. Eng., 2008, 3(2): 240-245.
[9] LIU Yusheng, LI Xingyuan. Robust adaptive output feedback control of nonlinearly parameterized systems[J]. Front. Electr. Electron. Eng., 2007, 2(3): 282-287.
[10] YANG Hong, ZHAO Jun. Robust controller for a class of uncertain switched fuzzy systems[J]. Front. Electr. Electron. Eng., 2007, 2(3): 334-337.
[11] YAN Quan, LI Xing-yuan, WANG Lu, LIU Hong-chao, CHEN Shu-heng. A robust adaptive control with unmodeled dynamic for HVDC transmission systems[J]. Front. Electr. Electron. Eng., 2006, 1(4): 371-374.
[12] LIU Yu-sheng, CHEN Jiang, LI Xing-yuan. Robust adaptive control of nonlinearly parameterized systems with unmodeled dynamics[J]. Front. Electr. Electron. Eng., 2006, 1(3): 259-264.
Viewed
Full text


Abstract

Cited
  Shared   
  Discussed