# ENHANCED MODEL-FREE PREDICTIVE CONTROL FOR VOLTAGE SOURCE INVERTERS USING AN ADAPTIVE OBSERVER

## DOI:

https://doi.org/10.59277/RRST-EE.2024.69.3.11## Keywords:

Active vector execution time (AVET), Model free predictive control (MFPC), Voltage source inverters (VSIs), Ultra-local model (ULM), Adaptive integrated sliding mode observe (AISMO), Cost-function, Zero vector## Abstract

In this paper, a free model predictive control based on the active vector execution time (AVET-MFPC) using an adaptive observer is proposed for two-level voltage source inverters. The traditional model-free predictive control (MFPC) uses the sampling period to select one voltage vector for all candidate vectors according to the minimizing cost function principle. With the proposed control, two vectors are selected at one sampling period. The first vector is an active vector that uses the execution time of the active vector to select it, while the second one is a zero vector as it is applied after the active vector. The execution time is calculated using the ultra-local model (ULM) equation. In the traditional MFPC, the factor in the ULM is chosen with approximate values ranging between ±50 % of the nominal value. This paper proposes an adaptive sliding mode observer (ASMO) with an improved design to observe the variation of this factor, especially in case of mismatch parameters and during a step change in the reference signal. Combining the proposed ASMO observer and the AVET-MFPC controller gives faster system response, good tracking results, and less computational burden. Finally, the effectiveness of the proposed control model is approved and confirmed under various conditions, as well as the simulations carried out and the results obtained.

## References

(1) C. Wang, D. Cao, X. Qu, C.Fan, An improved finite control set model predictive current control for a two-phase hybrid stepper motor fed by a three-phase VSI, Energies, 15, 3, p. 1222 (2022).

(2) F. Shiravani, P.Alkorta, J.A. Cortajarena, O. Barambones, An improved predictive current control for IM drives, Ain Shams Engineering Journal, 14, 8, p. 102037 (2023).

(3) M.S. Mousavi, S.A. Davari, V. Nekoukar, C. Garcia, J. Rodriguez, Model-free finite set predictive voltage control of induction motor, 12th Power Electronics, Drive Systems, and Technologies Conference (PEDSTC) (2021).

(4) M.A. Ilie, D. Floricău, Grid-connected photovoltaic systems with multilevel converters – modeling and analysis, Rev. Roum. Sci. Techn.– Électrotechn. et Énerg., 68, 1, pp. 77–83 (2023).

(5) J. Juan, G. Ignacio, J. Mario, G. Angel, C. Juan, Guiding the selection of multi-vector model predictive control techniques for multiphase drives, Machines, 12, 2, p. 115 (2024).

(6) X. Li, S. Zhang, X. Cui, Y. Wang, C. Zhang, Z. Li, Y. Zhou, Novel deadbeat predictive current control for PMSM with parameter updating scheme, IEEE Journal of Emerging and Selected Topics in Power Electronics, 10, 2, pp. 2065–2074 (2021).

(7) Z. Zhao, P. Davari, Y. Wang, F. Blaabjerg, Online capacitance monitoring for DC/DC boost converters based on low-sampling-rate approach, IEEE Journal of Emerging and Selected Topics in Power Electronics, 10, 5 pp. 5192–5204 (2021).

(8) R. Heydari, H. Young, Z. Rafiee, F. Flores-Bahamonde, M. Savaghebi, J. Rodriguez, Model-free predictive current control of a voltage source inverter based on identification algorithm, The 46th Annual Conference of the IEEE Industrial Electronics Society (IECON) (2020).

(9) W. Huang, Y. Huang, D. Xu, Model-free predictive current control of five-phase PMSM drives, Electronics, 12, 2, p. 4848 (2023).

(10) M. Kermadi, A Model-Free Predictive Current Controller for Voltage Source Inverters, Authorea Preprints (2023).

(11) M.S. Mousavi, S.A. Davari, V. Nekoukar, C. Garcia, J. Rodriguez, Model-free predictive control based on the integral sliding mode observer for induction motor, 13th Power Electronics, Drive Systems, and Technologies Conference (PEDSTC), IEEE (2022).

(12) P.V. Surjagade, S. Shimjith, A. Tiwari, Second order integral sliding mode observer and controller for a nuclear reactor, Nuclear Engineering and Technology, 52, 3, pp. 552–559 (2020).

(13) Z. Zhang, M. Leibold, A. Wollherr, Integral sliding-mode observer-based disturbance estimation for Euler–Lagrangian systems, IEEE Transactions on Control Systems Technology, 28, 6, pp. 2377–2389 (2019).

(14) A. Navid, K. Abbas, Second order sliding mode control for islanded ac microgrids with renewable power resources, Rev. Roum. Sci. Techn.– Électrotechn. et Énerg., 69, 1, pp. 39–44 (2024).

(15) J. Han, From PID to active disturbance rejection control, IEEE Transactions on Industrial Electronics, 56, 3, pp. 900–906 (2009).

(16) M.S. Mousavi, S.A. Davari, V. Nekoukar, C. Garcia, J. Rodriguez, A robust torque and flux prediction model by a modified disturbance rejection method for finite-set model-predictive control of induction motor, IEEE Transactions on Power Electronics, 36, 8, pp. 9322–9333 (2021).

(17) L. Medekhel, M. Hettiri, C.Labiod, K. Srairi, M. Benbouzid, Enhancing the performance and efficiency of two-level voltage source inverters: a modified model predictive control approach for common-mode voltage suppression, Energies, 16, 2, p. 7305 (2023).

(18) Z. Zhang, B. Li, R. Ma, X. Chen, Z. Dai, Finite control set model predictive control with a constant switching frequency for single‐phase grid‐connected photovoltaic inverter, IET Power Electronics, 15, 2, pp. 123–131 (2022).

(19) B. V. Comarella, D. Carletti, I. Yahyaoui, L.F. Encarnação, Theoretical and experimental comparative analysis of finite control set model predictive control strategies, Electronics, 12, 6, pp. 1482 ( 2023).

(20) A. Bakeer, G.Magdy, A. Chub, F. Jurado, M. Rihan, Optimal ultra-local model control integrated with load frequency control of renewable energy sources based microgrids, Energies, 15, 2, p. 9177 (2022).

(21) X. Li , Y.Wang, X. Guo, X.Cui, S. Zhang, Y. Li, An improved model-free current predictive control method for SPMSM drives, IEEE Access, 9, pp. 134672–134681 (2021).

(22) A. Abid, A. Bakeer, M. Bouzidi, A. Lashab, Model-free predictive current control for voltage source inverter: a comparative investigation, International Conference on Electrical Engineering and Advanced Technology (ICEEAT), IEEE (2023).

(23) Y. Wang, H. Li, R. Liu, L. Yang, X. Wang, Modulated model-free predictive control with minimum switching losses for PMSM drive system, IEEE Access, 8, pp. 20942–20953 (2020).

(24) O. Lăudatu, D. Niculae, M. Iordache, M.L. Bobaru, M. Stănculescu, Experimental analysis of power semiconductor elements used in flyback converters, Rev. Roum. Sci. Techn.– Électrotechn. et Énerg., 69, 1, pp. 67–72 (2024).

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*REVUE ROUMAINE DES SCIENCES TECHNIQUES — SÉRIE ÉLECTROTECHNIQUE ET ÉNERGÉTIQUE*,

*69*(3), 317-322. https://doi.org/10.59277/RRST-EE.2024.69.3.11