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Modeling of permanent magnet linear generator and state estimation based on sliding mode observer: a wave energy system application. (English) Zbl 07790655

Summary: This paper synopsis a new solution for Permanent Magnets Linear Generator (PMLG) state estimation subject to bounded uncertainty. Therefore, a PMLG modeling method is presented based on an equivalent circuit, wherein a mathematical model of the generator adapted to wave energy conversion is established. Then, using the Linear Matrix Inequality (LMI) optimization and a Lyapunov function, this system’s Sliding Mode Observer (SMO) design method is developed. Consequently, the proposed observer can give a robust state estimation. At last, numerical examples with and without uncertainty are included to exemplify the effectiveness and applicability of the suggested approaches.

MSC:

93B07 Observability

Software:

LMI toolbox
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Full Text: DOI

References:

[1] Ackermann, T., Wind Power in Power Systems., John Wiley and Sons, 2012
[2] Brooke, J., Wave Energy Conversion., Elsevier, 2003
[3] Calabrese, D.; Tricarico, G.; Brescia, E.; Cascella, G. L.; Monopoli, V. G.; Cupertino, F., Variable structure control of a small ducted wind turbine in the whole wind speed range using a Luenberger observer., MDPI, Energies 13 (2020), 4647
[4] Chen, W.; Saif, M., Unknown input observer design for a class of nonlinear systems: an LMI approach., Amer. Control Confer. (2006), 5
[5] Clément, A.; McCullen, P.; Falcão, A.; Fiorentino, A.; Gardner, F.; Hammarlund, K.; Lemonis, G.; Lewis, T.; Nielsen, K.; Petroncini, S.; others, Wave energy in Europe: current status and perspectives., Renewable Sustainable Energy Rev. 6 (2002), 405-431
[6] Falcao, A. F. de, Wave energy utilization: A review of the technologies., Elsevier 14 (2010), 899-918
[7] Farrok, O.; Islam, Md R.; Sheikh, Md R. I.; Guo, Y.; Zhu, J.; Jianguo; Lei, G., Oceanic wave energy conversion by a novel permanent magnet linear generator capable of preventing demagnetization., IEEE Trans. Industry Appl. 54 (2018), 6005-6014
[8] Foteinis, S., Wave energy converters in low energy seas: Current state and opportunities., Elsevier 162 (2022), 112448
[9] Gahinet, P.; Nemirovski, A.; Laub, A. J.; Chilali, M., LMI Control Toolbox, the MathWorks Inc, Natick., MA 1995
[10] Gao, Z.; Liu, X., An overview on fault diagnosis, prognosis and resilient control for wind turbine systems., MDPI J., Processes 9 (2021), 300
[11] Jayalakshmi, N. S.; Gaonkar, D. N.; Kumar, K. S. K., Dynamic modeling and performance analysis of grid connected PMSG based variable speed wind turbines with simple power conditioning system., IEEE Int. Confer. Power Electron. Drives Energy Systems (PEDES) (2012), 1-5
[12] Luenberger, D., An introduction to observers., IEEE Trans. Automat. Control 16 (1971), 596-602
[13] Mouni, E.; Tnani, S.; Champenois, G., Synchronous generator modelling and parameters estimation using least squares method., Simul- Modell. Practice Theory 16 (2008), 678-689
[14] Odgaard, P. F.; Stoustrup, J., Unknown input observer based detection of sensor faults in a wind turbine., IEEE Int. Confer. Control Appl. (2010), 310-315
[15] Polinder, H.; Mueller, M. A.; Scuotto, M.; Prado, M. G. de Sousa, Linear generator systems for wave energy conversion., In: Proc. 7th European Wave and Tidal Energy Conference, Porto 2007, pp. 11-14
[16] Remon, D.; Cantarellas, A. M.; Rodriguez, P., Equivalent model of large-scale synchronous photovoltaic power plants., IEEE Trans. Industry Appl. 52 (2016), 5029-5040
[17] Sename, O., New trends in design of observers for time-delay systems., Kybernetika 37 (2001), 427-458 · Zbl 1265.93108
[18] Simões, M. G.; Farret, F. A., Modeling and Analysis with Induction Generators., CRC Press 2014
[19] Tagliafierro, B.; Martínez-Estévez, I.; Domínguez, J.; Crespo, A. J. C.; Göteman, M.; Engström, J.; Gómez-Gesteira, M., A numerical study of a taut-moored point-absorber wave energy converter with a linear power take-off system under extreme wave conditions., Appl. Energy, Elsevier 311 (2022), 118629
[20] Trapanese, M.; Boscaino, V.; Cipriani, G.; Curto, D.; Dio, V. Di; Franzitta, V., A permanent magnet linear generator for the enhancement of the reliability of a wave energy conversion system., IEEE Trans. Industrial Electron. 66 (2018), 4934-4944
[21] Wang, Z.; Shen, Y.; Zhang, X.; Wang, Q., Observer design for discrete-time descriptor systems: An LMI approach., Systems Control Lett. 61 (2012), 683-687 · Zbl 1250.93038
[22] Wang, J.; Wang, F.; Wang, X.; Yu, L., Disturbance observer based integral terminal sliding mode control for permanent magnet synchronous motor system., Kybernetika 55 (2019), 586-603 · Zbl 1449.93024
[23] Wang, J.; Wang, F.; Wang, X.; Yu, L., Disturbance observer based integral terminal sliding mode control for permanent magnet synchronous motor system., Kybernetika 55 (2019), 586-603 · Zbl 1449.93024
[24] Zhang, Y.; Li, G., Non-causal linear optimal control of wave energy converters with enhanced robustness by sliding mode control., IEEE Trans. Sustainable Energy 11 (2019), 2201-2209
[25] Zhang, Y.; Li, G.; Zeng, T., Wave excitation force estimation for wave energy converters using adaptive sliding mode observer., IEEE Amer. Control Confer. (ACC) (2019), 4803-4808
[26] Zhang, Y.; Stansby, P.; Li, G., Non-causal linear optimal control with adaptive sliding mode observer for multi-body wave energy converters., IEEE Trans. Sustainable Energy 12 (2020), 568-577
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