Enhancing linear quadratic regulator and proportional-integral linear quadratic regulator controllers for photovoltaic systems

This article introduces the linear quadratic regulator (LQR) control and the hybrid linear quadratic regulator proportional-integral (LQR-PI) control, both applied to a photovoltaic system coupled with a DC-DC boost converter. The converter outputs direct current electrical energy to power direct loads. Two robust control correctors, based on the LQR and LQR-PI methods, are designed to enhance the static and dynamic performance of the PV DC-DC boost system. These controllers aim to minimize oscillations and overshoots while ensuring stability across varying solar conditions, thereby optimizing operation around the maximum power point. The disturb and observe maximum power point tracking (MPPT) technique, integrated with the LQR and LQR-PI controllers, ensures system functionality under disturbances. The novelty of this work lies in the development of a MATLAB control block diagram capable of regulating the reference voltage provided by the perturb and observe (P&O) MPPT algorithm. MATLAB simulations demonstrate the robustness and high performance of the LQR and LQR-PI controllers, validating the efficacy of this boost converter control strategy.

Authors

Publication Details

Journal
International Journal of Power Electronics and Drive Systems/International Journal of Electrical and Computer Engineering
Published
2025-05-23
DOI
https://doi.org/10.11591/ijece.v15i3.pp2713-2725
Citations
1
Primary Topic
Induction Heating and Inverter Technology
Type
article
Field-Weighted Citation Impact
0.71
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Enhancing linear quadratic regulator and proportional-integral linear quadratic regulator controllers for photovoltaic systems

Adel Bouchahed, Abdellah Draidi, Mohamed Assabaa, Boudjema Mehimmedetsi et al.
1 citations
International Journal of Power Electronics and Drive Systems/International Journal of Electrical and Computer Engineering
Induction Heating and Inverter Technology
0.71
article

Enhancing linear quadratic regulator and proportional-integral linear quadratic regulator controllers for photovoltaic systems

Adel Bouchahed, Abdellah Draidi, Mohamed Assabaa, Boudjema Mehimmedetsi, Ahmed Belhani
article en
1 citations

Abstract

This article introduces the linear quadratic regulator (LQR) control and the hybrid linear quadratic regulator proportional-integral (LQR-PI) control, both applied to a photovoltaic system coupled with a DC-DC boost converter. The converter outputs direct current electrical energy to power direct loads. Two robust control correctors, based on the LQR and LQR-PI methods, are designed to enhance the static and dynamic performance of the PV DC-DC boost system. These controllers aim to minimize oscillations and overshoots while ensuring stability across varying solar conditions, thereby optimizing operation around the maximum power point. The disturb and observe maximum power point tracking (MPPT) technique, integrated with the LQR and LQR-PI controllers, ensures system functionality under disturbances. The novelty of this work lies in the development of a MATLAB control block diagram capable of regulating the reference voltage provided by the perturb and observe (P&O) MPPT algorithm. MATLAB simulations demonstrate the robustness and high performance of the LQR and LQR-PI controllers, validating the efficacy of this boost converter control strategy.

International Journal of Power Electronics and Drive Systems/International Journal of Electrical and Computer EngineeringVol. 15(3)
Openalex Percentile: Top 32%
Induction Heating and Inverter Technology
0.71
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.