Robust nonlinear control via feedback linearization and Lyapunov theory for permanent magnet synchronous generator-based wind energy conversion system

Ridha CHEIKH, Arezki MENACER, L. CHRIFI-ALAOUI, Said DRID

PDF(1284 KB)
PDF(1284 KB)
Front. Energy ›› 2020, Vol. 14 ›› Issue (1) : 180-191. DOI: 10.1007/s11708-018-0537-3
RESEARCH ARTICLE
RESEARCH ARTICLE

Robust nonlinear control via feedback linearization and Lyapunov theory for permanent magnet synchronous generator-based wind energy conversion system

Author information +
History +

Abstract

In this paper, the method for the nonlinear control design of a permanent magnet synchronous generator based-wind energy conversion system (WECS) is proposed in order to obtain robustness against disturbances and harvest a maximum power from a typical stochastic wind environment. The technique overcomes both the problem of nonlinearity and the uncertainty of the parameter compared to such classical control designs based on traditional control techniques. The method is based on the differential geometric feedback linearization technique (DGT) and the Lyapunov theory. The results obtained show the effectiveness and performance of the proposed approach.

Keywords

permanent magnet synchronous generator / wind energy conversion system / stochastic / differential geometric / feedback linearization / maximum power point tracking / Lyapunov / robust control

Cite this article

Download citation ▾
Ridha CHEIKH, Arezki MENACER, L. CHRIFI-ALAOUI, Said DRID. Robust nonlinear control via feedback linearization and Lyapunov theory for permanent magnet synchronous generator-based wind energy conversion system. Front. Energy, 2020, 14(1): 180‒191 https://doi.org/10.1007/s11708-018-0537-3

References

[1]
Harrabi N, Souissi M, Aitouche A, Chabaane M. Intelligent control of wind conversion system based on PMSG using T-S Fuzzy Scheme. International Journal of Renewable Energy Research, 2015, 5(4): 52–60
[2]
Emna M E, Adel K, Mimouni M F. The wind energy conversion system using PMSG controlled by vector control and SMC strategies. International Journal of Renewable Energy Research, 2013, 3(1): 41–50
[3]
Munteanu I, Bratcu A I, Cutululis N A, Ceang Ă E. Optimal Control of Wind Energy Systems: Toward a Global Approach. London: Springer, 2008
[4]
Yadaiah N, Ramana N V. Linearization of multi-machine power system: modeling and control—a survey. International Journal of Electrical Power and Energy Systems, 2007, 29(4): 297–311
CrossRef Google scholar
[5]
Ghasemi S, Tabesh A, Askari-Marnani J. Application of fractional calculus theory to robust controller design for wind turbine generators. IEEE Transactions on Energy Conversion, 2014, 29(3): 780–787
CrossRef Google scholar
[6]
Tabesh A, Iravani R. On the application of the complex torque coefficients method to the analysis of torsional dynamics. IEEE Transactions on Energy Conversion, 2005, 20(2): 268–275
CrossRef Google scholar
[7]
Tabesh A, Iravani R. Frequency response analysis of torsional dynamics. IEEE Transactions on Power Systems, 2004, 19(3): 1430–1437
CrossRef Google scholar
[8]
Farmad M, Farhangi S, Gharehpetian G B, Afsharnia S. Nonlinear controller design for IPC using feedback linearization method. International Journal of Electrical Power & Energy Systems, 2013, 44(1): 778–785
CrossRef Google scholar
[9]
Boukhezzar B, Siguerdidjane H. Nonlinear control with wind estimation of a DFIG variable speed wind turbine for power capture optimization. Energy Conversion and Management, 2009, 50(4): 885–892
CrossRef Google scholar
[10]
Shi Z, Li X, Hu S. Direct feedback linearization based control in variable air volume air-conditioning system. Procedia Physics, 2012, 24(Part B): 1248–1254
CrossRef Google scholar
[11]
Bodson M, Chiasson J. Differential-geometric methods for control of electric motors. International Journal of Robust and Nonlinear Control, 1998, 8(11): 923–954
CrossRef Google scholar
[12]
Tailor M R, Bhathawala P H. Linearization of nonlinear differential equation by Taylor’s series expansion and use of Jacobian linearization process. International Journal of Theoretical and Applied Science, 2011, 4(1): 36–38
[13]
Jouybari-Moghaddam H, Hosseinian S H, Vahidi B. Grid reconnection detection for synchronous distributed generators in stand-alone operation. International Transactions on Electrical Energy Systems, 2015, 25(1): 138–154
CrossRef Google scholar
[14]
Akhrif O, Okou F A, Dessaint L A, Champagne R. Application of a multivariable feedback linearization scheme for rotor angle stability and voltage regulation of power systems. IEEE Transactions on Power Systems, 1999, 14(2): 620–628
CrossRef Google scholar
[15]
Lu Q, Sun Y Z. Nonlinear stabilizing control of multi machine systems. IEEE Transactions on Power Systems, 1988, 4(1): 36–38
CrossRef Google scholar
[16]
Hunt L R. Su R, Meyer G. Design for multi-input nonlinear systems in differential geometric control theory. Progress in Mathematics, 1982, 27:268–298
[17]
Isodori A. Nonlinear Control Systems. 3rd ed. Berlin: Springer-Verlag, 1995
[18]
Beschi M, Berenguel M, Visioli A, Guzmán J L, Yebra L J. Implementation of feedback linearization GPC control for a solar furnace. Journal of Process Control, 2013, 23(10): 1545–1554
CrossRef Google scholar
[19]
Yuan X, Chen Z, Yuan Y, Huang Y, Li X, Li W. Sliding mode controller of hydraulic generator regulating system based on the input/output feedback linearization method. Mathematics and Computers in Simulation, 2016, 119(C): 18–34
CrossRef Google scholar
[20]
Mahboub M A, Drid S, Sid M A, Cheikh R. Robust direct power control based on the Lyapunov theory of a grid-connected brushless doubly fed induction generator. Frontiers in Energy, 2016, 10(3): 298–307
CrossRef Google scholar
[21]
Zarchi H A, Arab Markadeh Gh R, Soltani J. Direct torque and flux regulation of synchronous reluctance motor drives based on input–output feedback linearization. Energy Conversion and Management, 2010, 14(1): 71–80
CrossRef Google scholar
[22]
Bouzidi M, Benaissa A, Barkat S. Hybrid direct power/current control using feedback linearization of three-level four-leg voltage source shunt active power filter. International Journal of Electrical Power and Energy Systems, 2014, 61: 629–646
CrossRef Google scholar
[23]
Mehrasa M, Pouresmaeil E, Akorede M F, Jorgensen B N, Catalão J P S. Multilevel converter control approach of active power filter for harmonics elimination in electric grids. Energy, 2015, 84: 722–731
CrossRef Google scholar
[24]
Alizadeh M, Kojori S S. Augmenting effectiveness of control loops of a PMSG (permanent magnet synchronous generator) based wind energy conversion system by a virtually adaptive PI (proportional integral) controller. Energy, 2015, 91: 610–629
CrossRef Google scholar
[25]
Drid S, Tadjine M, Nait-Said M S. Robust backstepping vector control for the doubly fed induction motor. IET Control Theory & Applications, 2007, 1(4): 861–868
CrossRef Google scholar
[26]
Mehrasa M, Pouresmaeil E, Zabihi S, Rodrigues E M G, Catalão J P S. A control strategy for the stable operation of shunt active power filters in power grids. Energy, 2016, 96: 325–334
CrossRef Google scholar
[27]
Phan D C, Yamamoto S. Rotor speed control of doubly fed induction generator wind turbines using adaptive maximum power point tracking. Energy, 2016, 111: 377–388
CrossRef Google scholar
[28]
Cheikh R, Menacer A, Drid S. Robust control based on the Lyapunov theory of a grid-connected doubly fed induction generator. Frontiers in Energy, 2013, 7(2): 191–196
CrossRef Google scholar
[29]
Bianchi F D. Wind Turbine Control Systems: Principles, Modeling and Gain Scheduling Design. London: Springer-Verlag, 2007
[30]
Nguyen H M, Naidu D S. Direct fuzzy adaptive control for standalone wind energy conversion systems. In: Proceedings of the World Congress on Engineering and Computer Science, 2012, San Francisco, USA
[31]
Nichita C. Study and development of structures and digital control laws for the realization of 3 kW wind turbine simulator. Dissertation for the Doctoral Degree. France: Université du Havre, 1995 (in French)
[32]
Welfonder E, Neifer R, Spanner M. Development and experimental identification of dynamic models for wind turbines. Control Engineering Practice, 1997, 5(1): 63–73
CrossRef Google scholar
[33]
Chapman J W, IIic M D, King C A, Eng L, Kaufman H. Stabilizing a multi machine power system via decentralized feedback linearizing excitation control. IEEE Transactions on Power Systems, 1993, 8(3): 830–839
CrossRef Google scholar

RIGHTS & PERMISSIONS

2018 Higher Education Press and Springer-Verlag GmbH Germany, part of Springer Nature
AI Summary AI Mindmap
PDF(1284 KB)

Accesses

Citations

Detail

Sections
Recommended

/