Issue |
E3S Web Conf.
Volume 619, 2025
3rd International Conference on Sustainable Green Energy Technologies (ICSGET 2025)
|
|
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Article Number | 03015 | |
Number of page(s) | 13 | |
Section | Smart Electronics for Sustainable Solutions | |
DOI | https://doi.org/10.1051/e3sconf/202561903015 | |
Published online | 12 March 2025 |
Servo Control of Shunt-Active Power Filters Using Kalman Filter With DC-Link Reference
1 EEE Department, Vignana Bharathi Institute of Technology, Hyderabad, India.
2 EEE Department, CMR college of Engineering & Technology, Hyderabad, India.
3 UG scholar, Vignana Bharathi Institute of Technology, Hyderabad, India.
4 UG scholar, Vignana Bharathi Institute of Technology, Hyderabad, India.
5 Department of Electrical and Electronics Engineering, Anurag University, Hyderabad, India.
6 EEE Department, Srinivasa Ramanujan Institute of Technology, Anantapur, India.
* Corresponding author: cvvijay93@gmail.com
LQG servo controllers may regulate current flow in a SAPF (shunt-active power filter) provided by a balanced or unbalanced supply voltage. Balanced or uneven supply voltages power the SAPF. The LQG controller’s Kalman filter (KF) and LQ regulator decrease output current inaccuracy and variability. LQG servo controller feedback compensators increase SAPF system tracking accuracy, gain stability, amplitude distortion, and sensitivity. This research study proposes a KF-based reference current generating technique to simplify proportional integral controller gain adjustment and remove voltage sensors. This reference approach may autonomously regulate adapting dc-link voltage anticipating current at most permissible source reference under varying load circumstances. Predictive modelling does this. MATLAB/Simulink integrates SAPF with the control algorithm. A LQRKF algorithm is compared against the LQG Servo KF technique to determine its efficacy. The simulation findings show that the proposed control method is superior than existing strategies for boosting resilience and lowering current harmonics in both steady-state and dynamic load circumstances. The results demonstrate that the technique out performs others.
Key words: LQG servo controller / Kalman filter (KF) / Gain stability / Dynamic load conditions
© The Authors, published by EDP Sciences, 2025
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