Unknown input observer-Model predictive control scheme for state and disturbance estimation of shunt active filter
DOI:
https://doi.org/10.22399/ijcesen.700Keywords:
Shunt active filter, Model predictive control, State estimation, Disturbance estimation, Proportional-Integral observerAbstract
The distribution system's nonlinear loads cause low total harmonic distortion (THD), low distortion power factor, and localized communication interference, among other poor power quality metrics. Shunt active power filter (SAPF) capacity to function depends on the controller's ability to follow the reference signal. To manage larger systems with several inputs and outputs, it would be challenging task to design PID controllers, because excessive controller gains would need to be tuned. Also, every control loop would operate independently of one another, as if there were no interactions between the two loops. This paper proffers Model prediction control for Shunt active power filter (SAPF), which can manage systems with several inputs and outputs that may interact with one another. Luenberger observer (LO) and Proportional Integral observer (PIO) fail to estimates the actual states of SAPF to SAPF, as shown even in the presence of three unknown disturbances, i.e step, triangular and noise type. The proposed unknown input observer (UIO) in the presence of three unknown disturbances perfectly tracks the reference signal. Apart from state estimation, the proposed observer also estimates all the unknown disturbances, when compared to PIO. The results have been simulated in MATLAB environment.
References
Padmanaban, S., Samavat, T., Nasab, M.A., Nasab, M.A., Zand, M. and Nikokar, F. (2023). Electric Vehicles and IoT in Smart Cities. In Artificial Intelligence-based Smart Power Systems (eds S. Padmanaban, S. Palanisamy, S. Chenniappan and J.B. Holm-Nielsen).
Mohsen Khalili, Mohammad Ali Dashtaki, Morteza Azimi Nasab, Hamid Reza Hanif, Sanjeevikumar Padmanaban & Baseem Khan | Wei Meng (Reviewing editor) (2022). Optimal instantaneous prediction of voltage instability due to transient faults in power networks taking into account the dynamic effect of generators, Cogent Engineering, 9(1);2072568, DOI:10.1080/23311916.2022.2072568
Amir Ali Dashtaki, Morteza Khaki, Mohammad Zand, Mostafa Azimi Nasab, P. Sanjeevikumar, Tina Samavat, Morteza Azimi Nasab, Baseem Khan. (2022). A Day Ahead Electrical Appliance Planning of Residential Units in a Smart Home Network Using ITS-BF Algorithm. International Transactions on Electrical Energy Systems, 2022;2549887. https://doi.org/10.1155/2022/2549887
D. A. Gonzalez and J. C. McCall. (1987). Design of Filters to Reduce Harmonic Distortion in Industrial Power Systems. in IEEE Transactions on Industry Applications, IA-23(3);504-511. doi: 10.1109/TIA.1987.4504938
Hirofumi Akagi; Edson Hirokazu Watanabe; Mauricio Aredes. (2017). Shunt Active Filters. in Instantaneous Power Theory and Applications to Power Conditioning, IEEE, 111-236. DOI:10.1002/9781119307181
M. P. Kazmierkowski and L. Malesani (1998). Current control techniques for three-phase voltage-source PWM converters: a survey. in IEEE Transactions on Industrial Electronics, 45(5);691-703. doi: 10.1109/41.720325.
S. Buso, L. Malesani and P. Mattavelli. (1998). Comparison of current control techniques for active filter applications. in IEEE Transactions on Industrial Electronics, 4(5);722-729. doi: 10.1109/41.720328
L. Malesani, P. Mattavelli and S. Buso. (1999). Robust dead-beat current control for PWM rectifiers and active filters. in IEEE Transactions on Industry Applications, 35(3);613-620. doi: 10.1109/28.767012.
S. M. Ali and M. P. Kazmierkowski. (1998). Current regulation of four leg PWM/VSI. in Proc. 24th Annu. Conf. IEEE Ind. Electron. Soc. (IECON’98) (Cat. No. 98CH36200), 3;1853–1858.
M. Dzieniakowski and M. Ka´zmierkowski. (1992). Microprocessor-based novel current regulator for VSI-PWM inverters. in Proc. 23rd Annu. IEEE Power Electron. Spec. Conf. (PESC’92), 1;459–464.
S. Kouro et al. (2010). Recent advances and industrial applications of multilevel converters. IEEE Trans. Ind. Electron., 57(8);2553–2580. doi: 10.1109/TIE.2010.2049719.
S. Bhattacharya, T. M. Frank, D. M. Divan, and B. Banerjee. (1998). Active filter system implementation. IEEE Ind. Appl. Mag., 4(5);47–63. DOI:10.1109/IAS.1996.560208
J. Rodriguez et al. (2007). Predictive Current Control of a Voltage Source Inverter. in IEEE Transactions on Industrial Electronics, 54(1);495-503. doi: 10.1109/TIE.2006.888802
S. Kouro, P. Cortés, R. Vargas, U. Ammann, and J. Rodríguez. (2009). Model predictive control—A simple and powerful method to control power converters. IEEE Trans. Ind. Electron., 56(6);1826–1838. doi: 10.1109/TIE.2008.2008349
Sunandha Rajagopal, & N. Thangarasu. (2024). The Impact of Clinical Parameters on LSTM-based Blood Glucose Estimate in Type 1 Diabetes . International Journal of Computational and Experimental Science and Engineering, 10(4);1233-1241. https://doi.org/10.22399/ijcesen.656
Downloads
Published
How to Cite
Issue
Section
License
Copyright (c) 2024 International Journal of Computational and Experimental Science and Engineering
This work is licensed under a Creative Commons Attribution 4.0 International License.