Journal of Energy Management and Technology

Journal of Energy Management and Technology

Adaptive Super-Twisting Controller for Voltage Regulation in a DC Microgrid

Document Type : Original Article

Authors
Mehdi Ashtari Mahin 1
Seyed Mehdi Hakimi 2
Seyed Vahid Naghavi 3
Vahid Behnamgol 2
1 Department of Electrical Engineering and Renewable Energy Research Centre, Damavand Branch, Islamic Azad University, Damavand, Tehran, Iran
2 Department of Electrical Engineering and Renewable Energy Research Centre, Damavand Branch, Islamic Azad University, Damavand, Iran
3 Digital Transformation Center, Research Institute of Petroleum Industry, Tehran, Iran
10.22109/jemt.2026.555273.1577
Abstract
Microgrids (MGs) typically function in two operational modes: on-grid and off-grid. The primary challenges in the off-grid mode involve voltage and frequency fluctuations or instability. To address these issues, an appropriate control system is required to regulate the microgrid’s voltage and frequency. Considering the system’s nonlinear characteristics, parameter uncertainties, and load variations, the use of nonlinear and robust control techniques is deemed an effective strategy. In this study, a nonlinear adaptive super-twisting controller based on sliding mode control (SMC) theory is developed to manage the microgrid. The main motivation for employing this controller is its ability to mitigate distortions under parameter uncertainties. To this end, the dynamic equations of the system are first derived, and subsequently, a controller is designed using the principles of SMC to ensure overall system control. To overcome the chattering phenomenon, an adaptive super-twisting algorithm is proposed. The closed-loop stability of the system is verified through the Lyapunov stability theorem. The effectiveness of the proposed method is assessed using MATLAB/Simulink simulations, and its performance is compared with conventional control approaches. The results demonstrate that the proposed adaptive super-twisting controller offers superior performance and practical applicability compared to traditional methods. The proposed controller is evaluated in an islanded (off-grid) DC microgrid configuration under load steps, irradiance variations, and battery parameter uncertainties. Simulation results demonstrate superior voltage regulation compared to a conventional super-twisting sliding mode controller and a PI controller, achieving a settling time below 0.18 s, an overshoot below 0.4%, and an RMSE of 0.42 V.
Keywords
microgrid
voltage regulation
nonlinear control
second order sliding mode control
super-twisting method
Subjects
[1]     Ashtari Mahini, M., Hakimi, S. M., Naghavi, S. V., & Behnamgol, V. (2025). Design of an Adaptive Super-Twisting Sliding Mode Controller to Adjust Voltage in DC Microgrids with Constant Power Load. Iranian Journal of Science and Technology, Transactions of Electrical Engineering, 49(1), 337-357.‏.
[2]     Thomas, T., Mishra, M. K., Kumar, C., & Liserre, M. (2024). Control of a PV-wind based DC microgrid with hybrid energy storage system using Lyapunov approach and sliding mode control. IEEE Transactions on Industry Applications, 60(2), 3746-3758.‏
[3]     Saifoddin,A , Mirzaei,N , Allahrabbi Shirazi,M and Yousefi,H . (2025). Comparative Applications of Supervised and Unsupervised Machine Learning Models in Energy Systems. Journal of Energy Management and Technology, 9(4), 284-290.
[4]     Moaven,M , Allahrabbi Shirazi,M and Ghodusinejad,M H . (2025). Systematic Analysis of the Impact of Life Cycle Assessment of Materials on Urban Heat Island Mitigation: A Path Toward Sustainable Urban Policy Using the PRISMA Method. Urban Development Policy Making, 2(1), 95-110.
[5]     Allah Rabbi Shirazi, M. A. (2024). Idea generation and examination of environmental challenges of floating solar photovoltaic power plants on wetlands and its economic advantage for local communities. Journal of sustainable Energy Systems, 3(1), 39-51.
[6]     Mohammadali Allahrabbi Shirazi, Rahim Zahedi, Hossein Yousefi, Alireza Aslani, Environmental and damage assessment of electric vehicles compared to internal combustion engine vehicles under various ambient temperature scenarios using the LCA approach, Energy Nexus, Volume 20, 2025, 100606, ISSN 2772-4271.
[7]     Allahrabbi Shirazi,M , Yousefi,H , Fathi,A and Baneshi,M . (2027). Urban Water Sustainability through Energy-Free Fog Water Harvesting: A Review of Fog-Collecting Systems. Urban Development Policy Making, 3(1), 69-94. doi: 10.22034/judpm.2025.558718.1073
[8]     Seyed Mohieddin Moezzi, Mohammadali Allahrabbi Shirazi, Alireza Rajabi Zadeh Monfared, Hossein Yousefi, Comparison of classical statistical models for forecasting CO₂ emissions, GDP, and TBL cancer indicators: A comparative analysis of East and West Asia, Energy Nexus, Volume 21, 2026, 100682, ISSN 2772-4271.
[9]     S. Hou, and T. Murata, "Multi-objective Demand Responding Micro Grid Dispatch Optimization based on Energy Storage Operation with Uncertain RES Power," Lecture Notes in Engineering and Computer Science: Proceedings of The International Multi Conference of Engineers and Computer Scientists 2021, 20-22 October, 2021, Hong Kong, pp190-195.
[10]  R. Pérez-Ibacache, C. A. Silva and A. Yazdani, “Linear State-Feedback Primary Control for Enhanced Dynamic Response of AC Microgrids”, IEEE Transactions on Smart Grid, Vol. 10, No. 3, 2019.
[11]  W. Ma, S. Ouyang, “Control strategy for inverters in microgrid based on repetitive and state feedback control”, International Journal of Electrical Power & Energy Systems, Vol. 111, 2019.
[12]  H. Jafari, et al., “Improved power sharing with a back-to-back converter and state-feedback control in a utility-connected microgrid,” 2018 IEEE Texas Power and Energy Conference (TPEC), College Station, 2018.
[13]  M. Armin, et al., “LMI Based Robust PID Controller Design for Voltage Control of Islanded Microgrid”, Asian Journal of Control, Vol. 20, 2018.
[14]  A. B. Siddique, M. S. Munsi, S. K. Sarker, S. K. Das, M. R. Islam, “Voltage and current control augmentation of islanded microgrid using multifunction model reference modified adaptive PID controller”, International Journal of Electrical Power & Energy Systems, Vol. 113, 2019.
[15]  G. Parise, L. Martirano, M. Kermani and M. Kermani, “Designing a power control strategy in a microgrid using PID / fuzzy controller based on battery energy storage,” IEEE International Conference on Environment and Electrical Engineering and IEEE Industrial and Commercial Power Systems Europe (EEEIC / I&CPS Europe), Milan, 2017.
[16]  H. Wang, et al., “Design of a Fractional Order Frequency PID Controller for an Islanded Microgrid: A Multi-Objective Extremal Optimization Method”, Energies, Vol. 10, 2017. 
[17]  M. Zolfaghari, M. Abedi and G. B. Gharehpetian, “Robust Nonlinear State Feedback Control of Bidirectional Interlink Power Converters in Grid-Connected Hybrid Microgrids,” IEEE Systems Journal, Vol. 14, No. 1, 2020.
[18]  S. Sen and V. Kumar, “Decentralized Output-Feedback-Based Robust LQR V-f Controller for PV-Battery Microgrid Including Generation Uncertainties,” IEEE Systems Journal, doi: 10.1109/JSYST.2020.2967774, 2020.
[19]  R. Heydari, et al., “Robust and Fast Voltage-Source-Converter (VSC) Control for Naval Shipboard Microgrids,” IEEE Transactions on Power Electronics, Vol. 34, No. 9, pp. 8299-8303, 2019.
[20]  T. V. Vu, D. Perkins, F. Diaz, D. Gonsoulin, C. S. Edrington, T. El-Mezyani, “Robust adaptive droop control for DC microgrids”, Electric Power Systems Research, Vol. 146, 2017.
[21]  A. Rezvani, M. Izadbakhsh, and M. Gandomkar, "Microgrid dynamic responses enhancement using artificial neural network genetic algorithm for photovoltaic system and fuzzy controller for high wind speeds", International Journal of Numerical Modelling, Vol. 29, 2016.
[22]  K. Tan, F. Lin, C. Shih and C. Kuo, “Intelligent Control of Microgrid With Virtual Inertia Using Recurrent Probabilistic Wavelet Fuzzy Neural Network,” IEEE Transactions on Power Electronics, Vol. 35, No. 7, 2020.
[23]  S. D. Kermany, M. Joorabian, S. Deilami and M. A. S. Masoum, “Hybrid Islanding Detection in Microgrid With Multiple Connection Points to Smart Grids Using Fuzzy-Neural Network,” IEEE Transactions on Power Systems, Vol. 32, No. 4, 2017.
[24]  M. S. Mahmoud, N. M. Alyazidi, M. I. Abouheaf, “Adaptive intelligent techniques for microgrid control systems: A survey”, International Journal of Electrical Power & Energy Systems, Vol. 90, 2017.
[25]  A. Mohammadzadeh, E. Kayacan, “A novel fractional-order type-2 fuzzy control method for online frequency regulation in ac microgrid”, Engineering Applications of Artificial Intelligence, Vol. 90, 2020.
[26]  F. Perez, A. Iovine, G. Damm and P. Ribeiro, “DC microgrid voltage stability by dynamic feedback linearization,” 2018 IEEE International Conference on Industrial Technology (ICIT), Lyon, 2018.
[27]  G. Lou, W. Gu, W. Sheng, X. Song and F. Gao, “Distributed Model Predictive Secondary Voltage Control of Islanded Microgrids With Feedback Linearization,” IEEE Access, Vol. 6, 2018.
[28]  Z. Guo, S. Li, and Y. Zheng, “Feedback Linearization Based Distributed Model Predictive Control for Secondary Control of Islanded Microgrid”, Asian Journal of Control, Vol. 22, 2020.
[29]  S. Yousefizadeh, et al., “Tracking Control for a DC Microgrid Feeding Uncertain Loads in More Electric Aircraft: Adaptive Backstepping Approach,” IEEE Transactions on Industrial Electronics, Vol. 66, No. 7, 2019.
[30]  M. Cucuzzella, G. P. Incremona and A. Ferrara, “Decentralized Sliding Mode Control of Islanded AC Microgrids with Arbitrary Topology,” IEEE Transactions on Industrial Electronics, Vol. 64, No. 8, 2017.
[31]  H. R. Baghaee, M. Mirsalim, G. B. Gharehpetian and H. A. Talebi, “A Decentralized Power Management and Sliding Mode Control Strategy for Hybrid AC/DC Microgrids including Renewable Energy Resources,” IEEE Transactions on Industrial Informatics, 2017.
[32]  H. R. Baghaee, M. Mirsalim, G. B. Gharehpetian and H. A. Talebi, “Decentralized Sliding Mode Control of WG/PV/FC Microgrids Under Unbalanced and Nonlinear Load Conditions for On- and Off-Grid Modes,” IEEE Systems Journal, Vol. 12, No. 4, 2018.
[33]  T. Li, Q. Cheng, “Structure analysis and sliding mode control of new dual quasi Z source inverter in microgrid”, International Transactions on Electrical Energy Systems”, Vol. 29, 2019.
[34]  T. Morstyn, A. V. Savkin, B. Hredzak and V. G. Agelidis, “Multi-Agent Sliding Mode Control for State of Charge Balancing Between Battery Energy Storage Systems Distributed in a DC Microgrid,” IEEE Transactions on Smart Grid, Vol. 9, No. 5, 2018.
[35]  P. Ge, Y. Zhu, T. Green and F. Teng, “Resilient Secondary Voltage Control of Islanded Microgrids: An ESKBF-Based Distributed Fast Terminal Sliding Mode Control Approach,” IEEE Transactions on Power Systems, 2020.
[36]  N. M. Dehkordi, N. Sadati, M. Hamzeh, “A backstepping high-order sliding mode voltage control strategy for an islanded microgrid with harmonic/interharmonic loads”, Control Engineering Practice, Vol. 58, 2017.
[37]  D. Xu, Y. Dai, C. Yang, X. Yan, “Adaptive fuzzy sliding mode command-filtered backstepping control for islanded PV microgrid with energy storage system”, Journal of the Franklin Institute, Vol. 356, No. 4, 2019.
[38]  D. Xu, W. Zhang, B. Jiang, P. Shi and S. Wang, “Directed-Graph-Observer-Based Model-Free Cooperative Sliding Mode Control for Distributed Energy Storage Systems in DC Microgrid,” IEEE Transactions on Industrial Informatics, Vol. 16, No. 2, 2020.
[39]  H. Li, X. Wang and J. Xiao, “Adaptive Event-Triggered Load Frequency Control for Interconnected Microgrids by Observer-Based Sliding Mode Control,” IEEE Access, Vol. 7, 2019.
[40]  B. Yang, J. Wang, Y. Sang, L. Yu, H. Shu, Sh. Li, T. He, L. Yang, X. Zhang, T. Yu, “Applications of supercapacitor energy storage systems in microgrid with distributed generators via passive fractional-order sliding-mode control”, Energy, Vol. 187, 2019.
[41]  S. Chaturvedi, D. Fulwani and J. M. Guerrero, “Adaptive-Sliding-Mode-Control based Output Impedance Shaping for Ripple Management in DC Microgrids Affected by Inverter Loads,” IEEE Transactions on Sustainable Energy, 2020.
[42]  Khalil, H. K. (2002). Nonlinear systems (3rd ed.). Prentice Hall.
[43]  Behnamgol, V., Asadi, M., Mohamed, M. A., Aphale, S. S., & Faraji Niri, M. (2024). Comprehensive review of lithium-ion battery state of charge estimation by sliding mode observers. Energies, 17(22), 5754.‏.
[44]  Behnamgol, V., Asadi, M., Aphale, S. S., & Sohani, B. (2025). Recursive PID-NT Estimation-Based Second-Order SMC Strategy for Knee Exoskeleton Robots: A Focus on Uncertainty Mitigation. Electronics, 14(7), 1455.‏
[45]  V. Behnamgol, A. R. Vali, A. Mohammadi and A. Oraee, “Lyapunov-based Adaptive SmoothSecondorder Sliding Mode Guidance Law with Proving Finite Time Stability”, Journal of Space Science and Technology, Vol. 11, No. 2, Summer 2018.
[46]  Behnamgol, V., Asadi, M., & Aphale, S. S. (2025). Adaptive sliding mode control with fixed-time stability for robust glucose regulation. International Journal of Dynamics and Control, 13(4), 157.‏
[47]  Kassim, S. O., Zou, J., Behnamgol, V., Vaziri, V., & Aphale, S. S. (2025). Enhancing wide-band trajectory tracking and finite-time control of Dielectric Elastomer Actuators using Nonsingular terminal sliding mode control scheme. Mechatronics, 109, 103336.‏
[48]  F. Perez, et al., "Nonlinear Control for Isolated DC MicroGrids", Revue Africaine de la Recherche en Informatique et Mathématiques Appliquées, INRIA, Vol. 30, 2019.‏
Journal of Energy Management and Technology
Volume 10, Issue 2
Spring 2026
Pages 99-113

  • Receive Date 24 October 2025
  • Revise Date 12 June 2026
  • Accept Date 20 June 2026