PABITRA KUMAR BISWAS

Pabitra Kumar Biswas completed his B.Tech from WBUT, India. He received his ME. Degree 2007 from IIEST, West Bengal and PhD. Degree in Electrical Engineering on 2013 from NIT, Durgapur. He is presently working as an Associate Professor in Electrical and Electronics Engineering in NIT, Mizoram. He is also Associate Dean (R&C). He has published a numbers of research papers in National/International Conference and Records/Journals. He has a book and more than 6 book chapters and filed three patents. He has completed one DST-SERB project. He has about 15 years of academic as well as research experience. He has guided 7 Ph.D students and more than 10 M.Tech students and Ten more are pursuing their research at present. He has reviewed papers in reputed International Conference and Journals. His research interests include Electromagnetic Levitation System, Active Magnetic Bearing, Power electronics Converters, PMSM and BLDC Motor Drives, Electric Vehicles and Renewable energy.

RESEARCH INTERESTS

lectromagnetic Levitation system, Active magnetic bearing, Power Electronics converters , Vector control and sensor less control of Induction motor,PMSM and BLDC motor Drives,Renewable energy system and E-Vehicles

Scopus Publications

Advancements and Challenges in Active Magnetic Bearings: A Comprehensive Review of Performance, Control, and Future Prospects
Debarghya Dutta, Pabitra Kumar Biswas, Sukanta Debnath, and Furkan Ahmad
Institute of Electrical and Electronics Engineers (IEEE)
This paper provides an in-depth assessment of Active Magnetic Bearings (AMBs), which are electromagnetic bearings powered by power electronic components for high-speed equipment. The paper highlights the advantages of AMBs as frictionless bearings that utilize magnetic force to support the rotor, resulting in reduced wear, lower losses, and extended lifespan compared to classical ball bearings. AMBs are particularly well-suited for high-speed applications and demonstrate compatibility with both clean environments, such as renewable energy sectors, and challenging conditions like extreme pressures, temperatures, and harsh environments. However, controlling AMBs presents difficulties due to their nonlinear and inherently unstable nature. The paper focuses on examining the benefits and drawbacks of AMBs, including fault analyses. It further emphasizes recent advancements in power electronics supervision, including quick-switching power components, power conversion devices, and advanced control techniques, which have significantly expanded the potential applications of AMBs across various industries. Additionally, the paper explores the electromagnetic setups, electrical converters, sensors, and optimization techniques employed in AMBs, providing valuable insights into their construction, fault-finding methods, control strategies, and ongoing and future research trends.


A robust MPPT framework based on GWO-ANFIS controller for grid-tied EV charging stations
Debabrata Mazumdar, Pabitra Kumar Biswas, Chiranjit Sain, Furkan Ahmad, and Luluwah Al-Fagih
Springer Science and Business Media LLC
AbstractAs electric vehicles gain popularity, there has been a lot of interest in supporting their continued development with the aim of enhancing their dependability, environmental advantages, and charging efficiency. The scheduling of navigation and charging for electric vehicles is among the most well-known research topics. For optimal navigation and charging scheduling, the coupled network state between the transportation and power networks must be met; moreover, the scheduling outcomes might significantly impact these networks. To address climate challenges, relying only on fossil fuel-based infrastructure for electric car charging is insufficient. Consequently, Multi-Energy Integrated EV charging stations have emerged as a workable solution that seamlessly integrates grid power, renewable energy sources—particularly solar energy—and EV charging needs. The enhanced grey wolf optimised (GWO) ANFIS controller for Maximum Power Point Tracking (MPPT), standby battery systems, solar power, neural network-integrated grids, and sophisticated control algorithms like PID controller are all proposed in this article as energy-efficient charging terminals for electric vehicles. Moreover, authors had considered four conditional case study and with the help of MATLAB/Simulink 2018a software, the design is thoroughly examined and assessed, providing a viable route for an efficient and sustainable EV charging infrastructure.


Optimal electric vehicle charge scheduling algorithm using war strategy optimization approach
Vikramgoud Madaram, Pabitra Kumar Biswas, Chiranjit Sain, Sudhakar Babu Thanikanti, and Shitharth Selvarajan
Springer Science and Business Media LLC



A comprehensive analysis of the optimal GWO based FOPID MPPT controller for grid-tied photovoltaics system under atmospheric uncertainty
Debabrata Mazumdar, Pabitra Kumar Biswas, Chiranjit Sain, Furkan Ahmad, and Luluwah Al-Fagih
Elsevier BV



Advancement of electric vehicle technologies, classification of charging methodologies, and optimization strategies for sustainable development - A comprehensive review
Vikram Goud Madaram, Pabitra Kumar Biswas, Chiranjit Sain, Sudhakar Babu Thanikanti, and Praveen Kumar Balachandran
Elsevier BV



Developing a resilient framework for electric vehicle charging stations harnessing solar energy, standby batteries and grid integration with advanced control mechanisms
Debabrata Mazumdar, Pabitra K. Biswas, Chiranjit Sain, Furkan Ahmad, and Luluwah Al‐Fagih
Wiley
AbstractA direct consequence of the rapid expansion of civilization and modernization trends is the escalation in global warming and the consequential climatic upheavals. The world has actively advocated the adoption of electric vehicles (EVs) as a response to the environmental challenges posed by vehicular emissions. It is evident that conventional fuel‐based charging infrastructures are economically impractical and lack organizational cohesion in light of the proliferation of EVs. An EV charging station powered by renewable energy presents a promising opportunity for enhancing flexibility and control. It is imperative that EV charging stations be equipped with solar power and standby batteries (SBBs). Consequently, this article presents and evaluates a system that utilizes a proportional‐integral‐derivative controller, a neural network‐equipped grid and a charging station utilizing a Dragon Fly Optimization Algorithm to generate power and a maximum power point tracking controller. To achieve optimal power management within the charging station, MATLAB/Simulink is used to implement and rigorously test the proposed system. It orchestrates the interaction between the solar panel, backup battery, grid and EVs. Compared to existing systems in the literature, the comprehensive system exhibits commendable efficiency. Due to the pivotal role played by grid integration and the SBB, the system can ensure a reliable power supply to the charging station under any weather conditions.


Design and Development of Bidirectional Converter based on V2G and G2V Operation
Akanksha Yadagiri, Mahendar Meadari, D. Harsha, Pabitra Kumar Biswas, and Thanikanti Sudhakar Babu
EDP Sciences
The rapid progression of electric vehicles (EVs) in the transportation sector poses a potential challenge of increased peak energy demand on existing grid structures. Consequently, the significance of V2G power conversion technology becomes paramount in managing sudden surges in energy requirements. To address this issue, the authors propose a “Bidirectional Converter Based on V2G and G2V Operation” which focuses on facilitating energy transfer between vehicles and the grid through bidirectional converters, catering to both V2G and G2V operations. In this work, the authors analyzed a bidirectional buck-boost converter interface with an H bridge AC/DC converter together with the related control method in a reduced topology. The efficiency of the developed system is evaluated with the help of a developed simulation model in MATLAB/SIMULINK. The developed model was tested under various conditions and was able to perform effectively.


Performance analysis of drone sqadron optimisation based MPPT controller for grid implemented PV battery system under partially shaded conditions
Debabrata Mazumdar, Pabitra Kumar Biswas, Chiranjit Sain, Furkan Ahmad, Taha Selim Ustun, and Akhtar Kalam
Elsevier BV



Bi-LSTM predictive control-based efficient energy management system for a fuel cell hybrid electric vehicle
Debasis Chatterjee, Pabitra Kumar Biswas, Chiranjit Sain, Amarjit Roy, F. Ahmad, and Jagdeep Rahul
Elsevier BV



Comparative analysis of single-coil and double-coil active magnetic bearings for high-speed application
S. Debnath, U. Das, and P. K. Biswas
Springer Science and Business Media LLC



Design and speed control of U-type 3-coil active magnetic bearing
Jonathan Laldingliana, Sukanta Debnath, Pabitra Kumar Biswas, and Upama Das
Springer Science and Business Media LLC



Design and Analysis of Bidirectional Charging Stations for Sustainability Roadmap for Smart Electric Vehicles
Sarasij Adhikary and Pabitra Kumar Biswas
Wiley



Design and Testing of U-type Electromagnetic Actuator for Magnetic Bearing
Sukanta Debnath, Upama Das, and Pabitra Kumar Biswas
Springer Nature Singapore



A Wavelet-Based Analysis for Monitoring Controller Reliability in Active Magnetic Bearing with Rotor Eccentricities
Debarghya Dutta, Pabitra Kumar Biswas, Sukanta Debnath, and Furkan Ahmad
Institute of Electrical and Electronics Engineers (IEEE)



Exact analytic technique for designing controller architecture in multi-axis active magnetic bearings with rotor eccentricities
Debarghya Dutta, Sukanta Debnath, and Pabitra Kumar Biswas
Informa UK Limited



Design, simulation and testing of U-type actuator-based single-coil active-magnetic-bearing
Upama Das, Sukanta Debnath, Suraj Gupta, Pabitra Kumar Biswas, Sujit Kumar Biswas, and Thanikanti Sudhakar Babu
Informa UK Limited



Artificial Neural Network Based Holistic Approach in Energy Management Controllers for Fuel Cell Hybrid Electric Vehicles
Debasis Chatterjee, Pabitra Kumar Biswas, Chiranjit Sain, and Amarjit Roy
IEEE
Fuel Cell Hybrid Electric Vehicles (FCHEVs) have emerged as encouraging substitutes for conventional vehicles due to their lower environmental impact and higher energy efficiency. Effective energy management is crucial for optimizing the performance of FCHEVs. This paper presents an Artificial Neural Network (ANN) based holistic approach for energy management controllers in FCHEVs. The proposed approach leverages ANN models trained on real-world driving data to predict optimal power distribution between the fuel cell and battery. By utilizing ANN's ability to learn complex patterns in data, the proposed approach aims to improve energy utilization, enhance vehicle performance, and reduce environmental impact. Simulation results demonstrate the effectiveness of the ANN -based approach, showing significant improvements in energy efficiency compared to traditional control strategies. The findings suggest that ANN -based energy management controllers have the potential to advance the efficiency and sustainability of FCHEVs, contributing to a cleaner and greener transportation ecosystem.


Introduction to Novel GWO-FOPID MPPT Approach in Grid Integrated Sustainable PV MPPT Architecture
Debabrata Mazumdar, Pabitra Kumar Biswas, and Chiranjit Sain
IEEE
In recent years, growing consumer demand for sustainable energy is driving down costs and paving the way for more clean energy in the future. Grid implementation is necessary here due to erratic atmospheric scenario. The root causes of the issue include variable sources, daytime costs, and restrictions on solar panel specifications. In order to increase the performance and reliability of power systems, an integration of storage devices for energy into the power system structure is suggested in this article. A fractional order PID (FOPID) controller connected with grid implemented solar PV system has been developed in this article. This controller is designed to maximise the amount of power generated by the solar energy source. With the adaptive feature of a conventional PID controller, the developed controller can optimise the gain parameter by taking grid side and generator parameters into account. Grey Wolf Optimisation (GWO) was used in the proposed study to tune the FOPID controller for maximum power point tracking. The objective of this study is to maximise solar power output in a range of weather conditions. This will confirm the effectiveness of the suggested controller. The flying squirrel search optimisation (FSSO), PSO tune FOPID controllers, and fuzzy logic controllers (FLC) are used to compare the performance of the developed method.


Bidirectional operation of electric vehicle charger incorporating grids and home energy storage: V2G/G2V/V2H/V2X for sustainable development
Sarasij Adhikary, Pabitra Kumar Biswas, Thanikanti Sudhakar Babu, and Mallala Balasubbareddy
Elsevier



Performance Analysis of Optimized Non-Linear Discrete PID MPPT for Efficient Battery Charging Incorporated with Grid
Anupama Ganguly, Pabitra Kumar Biswas, Sarasij Adhikary, Pradipta Acharya, and Suraj Gupta
IEEE
In power system networks, utilizing renewable energy resources has become more common within the past few years. Compared to several renewable sources like wind, geothermal, biomass, tidal etc, the solar proves to be the best choice because of its cleanliness and non-polluting nature. But to overcome its major shortcoming that is intermittency, it's a mandate to incorporate a storage device like battery, super capacitor, fuel cell etc. with the solar power generation. The development of a nonlinear discrete PID (NDPID)to be served as an MPPT controller for photovoltaic (PV) generation systems working in erratic climatic conditions is the subject of this article. The optimal NDPID gains which are found by Mountain Gazelle Optimization (MGO), help to drive the variable step of the conventional Perturb & Observe (Pb&O). In addition with, For optimal power control in the battery charging strategy, a PI controller, in association with grid accompanied by current governing topology, and a functional charging platform built with MGO-optimized NDPID-based rearrange able step size Pb&O to be acted as the efficient MPPT controller are implemented and verified in MATLAB/Simulink. Additionally, when compared to other current systems that have been studied in the literature, the introduced system as a whole demonstrates superior efficacy. Lastly, because grid integration is essential to the total demand, this suggested approach guarantees that the charging scheme is solely capable of delivering power even during erratic weather by sustaining the voltage of DC link.


Optimization of PID Tuning of DC-DC Bidirectional Converter Control Strategy for EV Charger using GA and IoT based SOC Estimation
Sarasij Adhikary and Pabitra Kumar Biswas
IEEE
Electric Vehicle (EV) charger combines power electronics devices with a control scheme consisting of an AC to DC converter for rectification and DC to DC converter for required voltage level. The objective presents to put the desired level of output. Bi-directional converter of DC to DC operation charges EV battery by taking energy of DC link voltage, and for discharging of battery, the DC to DC converter feeds 800V dc. Here DC-DC converter (non-isolated) designed and implemented for bidirectional function. The converter controlling scheme is created by a tune PID controller encapsulated by genetic algorithm based gain defining to get less integral time absolute error (ITAE). To charge the battery and discharging as an integral part of the grid to vehicle (G2V) method to support peak load and grid to vehicle (G2V) as conventional charging. The EV battery parameters are monitored, and the expected time of completion of charge is calculated and represented. SOC estimation and estimated charging time are done by the coulomb counting method. Battery SOC, charger rating, and expected completion time of charging are all put into the cloud storage in ThingSpeak for monitoring purposes. The stored data is used for analysis and visualization using internet of things (IoT).


A Comprehensive Review Based on Conventional and Artificial Intelligence Strategies for MPPT-Based Solar PV System
Debabrata Mazumdar, Chiranjit Sain, and Pabitra Kumar Biswas
Springer Nature Singapore



An IoT Based Smart Parking Lot Allocation & Monitoring System for Bidirectional Charging Station with V2G and G2V Operational Capability for Electric Vehicle in Matlab/Simulink
Sarasij Adhikary and Pabitra Kumar Biswas
IEEE
EV charging time is one of the significant limitations that has to be overcome by managing the charging time and utilizing the parking time of the EV. Except for commercial vehicles, most personal cars are parked 70 -80% of the time of the day. The cities have a parking lot management system to solve the parking problem by developing an intelligent IoT-based parking lot with a V2G-enabled system. The parking system is modelled to check the occurrence of the EV at the parking lot, and the V2G operation is implemented and presented in this paper. A bidirectional AC-DC converter transfers energy from the grid to the vehicle and vice versa. This MATLAB model is connected to a cloud-based platform named Things Speak to check the system occupancy with the expected completion time. This system enables the EV and the charging station to share different parameters through the cloud. This model is validated by checking the system through a web application/android application, and validation of the V2G model is implemented and analyzed.


PDMS-based multilayer antireflective radiative cooler for the commercial solar module
Avinash Kumar, Pabitra Kumar Biswas, and Amartya Chowdhury
Informa UK Limited



Optimizing MPPT Control for Enhanced Efficiency in Sustainable Photovoltaic Microgrids: A DSO-Based Approach
Debabrata Mazumdar, Pabitra Kumar Biswas, Chiranjit Sain, Furkan Ahmad, Rishiraj Sarker, and Taha Selim Ustun
Hindawi Limited
The output of photovoltaic (PV) systems is significantly impacted by the vagaries of ambient temperature, solar irradiance, and environmental fluctuations. To achieve the utmost attainable power from PV systems, it is desired to be efficient at the maximum power point in diverse weather climates. Maximum power point tracking (MPPT) is used to schedule a designated location from where the highest power can be harvested. In the context of solar photovoltaic systems connected with DC microgrid platforms, this study introduces a recently developed drone squadron optimization (DSO) scheme that tracks the global maximum power point under PSCS difficulties. Furthermore, an exhaustive comparative analysis has been presented among particle swarm optimization (PSO), cuckoo search algorithm (CUSA), and grey wolf optimization (GWO) under different operating environments to endorse the supremacy of the nominated technique. The suggested method performs noticeably faster than many other methods currently in use, and in addition to offering the highest power, it can also use bidirectional power flow regulation in both constant and variable air conditions. Lastly, an MPPT system interfaced with the DC microgrid based on DSO ensures a sustainable and reliable architecture to provide at load in low power generating situations.

RECENT SCHOLAR PUBLICATIONS

Design and Analysis of Bidirectional Charging Stations for Sustainability Roadmap for Smart Electric Vehicles
S Adhikary, PK Biswas
Smart Electric and Hybrid Vehicles: Advancements in Materials, Design 2025



A robust MPPT framework based on GWO-ANFIS controller for grid-tied EV charging stations
D Mazumdar, PK Biswas, C Sain, F Ahmad, L Al-Fagih
Scientific Reports 14 (1), 30955 2024



Advancements and Challenges in Active Magnetic Bearings: A Comprehensive Review of Performance, Control and Future Prospects
D Dutta, PK Biswas, S Debnath, F Ahmad
IEEE Access 2024



A Wavelet-Based Analysis for Monitoring Controller Reliability in Active Magnetic Bearing With Rotor Eccentricities
D Dutta, PK Biswas, S Debnath, F Ahmad
IEEE Access 2024



Exact analytic technique for designing controller architecture in multi-axis active magnetic bearings with rotor eccentricities
D Dutta, S Debnath, PK Biswas
Mechanics Based Design of Structures and Machines, 1-19 2024



Comparative performance analysis of energy management techniques for fuel cell hybrid electric vehicles
D Chatterjee, PK Biswas, C Sain
Intelligent Computation and Analytics on Sustainable Energy and Environment 2024



PDMS-based multilayer antireflective radiative cooler for the commercial solar module
A Kumar, PK Biswas, A Chowdhury
International Journal of Green Energy 21 (14), 3188-3200 2024



Design, simulation and testing of U-type actuator-based single-coil active-magnetic-bearing
U Das, S Debnath, S Gupta, PK Biswas, SK Biswas, TS Babu
Mechanics Based Design of Structures and Machines, 1-17 2024



Advancement of electric vehicle technologies, classification of charging methodologies, and optimization strategies for sustainable development-a comprehensive review
M VikramGoud, PK Biswas, C Sain, TS Babu, PK Balachandran
Heliyon 2024



Developing a resilient framework for electric vehicle charging stations harnessing solar energy, standby batteries and grid integration with advanced control mechanisms
D Mazumdar, PK Biswas, C Sain, F Ahmad, L Al‐Fagih
Energy Science & Engineering 12 (10), 4355-4370 2024



Introduction to Novel GWO-FOPID MPPT Approach in Grid Integrated Sustainable PV MPPT Architecture
D Mazumdar, PK Biswas, C Sain
2024 IEEE 4th International Conference on Sustainable Energy and Future 2024



Performance Analysis of Optimized Non-Linear Discrete PID MPPT for Efficient Battery Charging Incorporated with Grid
A Ganguly, PK Biswas, S Adhikary, P Acharya, S Gupta
2024 IEEE International Conference on Information Technology, Electronics 2024



Performance analysis of drone sqadron optimisation based MPPT controller for grid implemented PV battery system under partially shaded conditions
D Mazumdar, PK Biswas, C Sain, F Ahmad, TS Ustun, A Kalam
Renewable Energy Focus 49, 100577 2024



Bi-LSTM predictive control-based efficient energy management system for a fuel cell hybrid electric vehicle
D Chatterjee, PK Biswas, C Sain, A Roy, F Ahmad, J Rahul
Sustainable Energy, Grids and Networks 38, 101348 2024



SVM classifier based energy management strategy for dual‐source fuel cell hybrid electric vehicles
D Chatterjee, PK Biswas, C Sain, A Roy, MM Islam, TS Ustun
The Journal of Engineering 2024 (6), e12392 2024



An IoT Based Smart Parking Lot Allocation & Monitoring System for Bidirectional Charging Station with V2G and G2V Operational Capability for Electric Vehicle in Matlab/Simulink
S Adhikary, PK Biswas
2024 IEEE 13th International Conference on Communication Systems and Network 2024



Design and speed control of U-type 3-coil active magnetic bearing
J Laldingliana, S Debnath, PK Biswas, U Das
Electrical Engineering 106 (2), 1135-1145 2024



Energy Conservation in a Domestic Household Through Audit Recommendation
A Arya, A Bhattacharya, PK Biswas
2024 2nd International Conference on Disruptive Technologies (ICDT), 1656-1661 2024



Design and Testing of U-type Electromagnetic Actuator for Magnetic Bearing
S Debnath, U Das, PK Biswas
International Conference on Power Engineering and Intelligent Systems (PEIS 2024



Bidirectional operation of electric vehicle charger incorporating grids and home energy storage: V2G/G2V/V2H/V2X for sustainable development
S Adhikary, PK Biswas, TS Babu, M Balasubbareddy
Renewable Energy for Plug-In Electric Vehicles, 191-207 2024

MOST CITED SCHOLAR PUBLICATIONS

Modelling and Comparative Dynamic Analysis due to Demagnetization of a Torque Controlled Permanent Magnet Synchronous Motor Drive for Energy-Efficient Electric Vehicle
PKB Chiranjit Sain, Atanu Banerjee
ISA Transactions, Elsevier 2019
Citations: 33



Design, analysis, and testing of I-type electromagnetic actuator used in single-coil active magnetic bearing
S Debnath, PK Biswas
Electrical Engineering 103 (1), 183-194 2021
Citations: 30



Design and optimisation of a fuzzy-PI controlled modified inverter-based PMSM drive employed in a light weight electric vehicle
C Sain, A Banerjee, PK Biswas, AT Azar, TS Babu
International Journal of Automation and Control 16 (3-4), 459-488 2022
Citations: 28



Updated PSO optimised fuzzy‐PI controlled buck type multi‐phase inverter‐based PMSM drive with an over‐current protection scheme
C Sain, A Banerjee, P Kumar Biswas, T Sudhakar Babu, T Dragicevic
IET electric power applications 14 (12), 2331-2339 2020
Citations: 26



Bidirectional converter based on G2V and V2G operation with time of usage-based tariff analysis and monitoring of charging parameters using IoT
S Adhikary, PK Biswas, C Sain, SB Thanikanti, NI Nwulu
Energy Reports 9, 5404-5419 2023
Citations: 25



Artificial intelligence based fractional order PID control strategy for active magnetic bearing
J Laldingliana, PK Biswas
Journal of Electrical Engineering & Technology 17 (6), 3389-3398 2022
Citations: 23



Techno-commercial analysis of sustainable E-bus-based public transit systems: An Indian case study
S Majumder, K De, P Kumar, B Sengupta, PK Biswas
Renewable and Sustainable Energy Reviews 144, 111033 2021
Citations: 23



Advanced magnetic bearing device for high-speed applications with an I-type electromagnet
S Debnath, PK Biswas
Electric Power Components and Systems 48 (16-17), 1862-1874 2021
Citations: 22



Closed Loop control of Active Magnetic Bearing using PID controller
SDPKB Suraj Gupta, Jonathan Laldingliana
IEEE International Conference on Computing, Power and Communication 2018
Citations: 22



Efficient energy management strategy for fuel cell hybrid electric vehicles using classifier fusion technique
D Chatterjee, PK Biswas, C Sain, A Roy, F Ahmad
IEEE Access 11, 97135-97146 2023
Citations: 21



Analysis and Simulation of PWM Based Power Amplifier for Single Axis Active Magnetic Bearing (AMB)
PKBJL Sukanta Debnath
International Transportation Electrification Conference, 1-5 2017
Citations: 19



Metaheuristic optimization techniques used in controlling of an active magnetic bearing system for high-speed machining application
S Gupta, PK Biswas, S Debnath, A Ghosh, TS Babu, HM Zawbaa, ...
IEEE Access 11, 12100-12118 2023
Citations: 18



Modern DC–DC power converter topologies and hybrid control strategies for maximum power output in sustainable nanogrids and picogrids—a comprehensive survey
A Ganguly, PK Biswas, C Sain, TS Ustun
Technologies 11 (4), 102 2023
Citations: 17



An improved low‐voltage ride‐through (LVRT) strategy for PV‐based grid connected inverter using instantaneous power theory
S Bagchi, D Chatterjee, R Bhaduri, PK Biswas
IET Generation, Transmission & Distribution 15 (5), 883-893 2021
Citations: 17



Control of an active magnetic bearing system using swarm intelligence-based optimization techniques
S Gupta, S Debnath, PK Biswas
Electrical Engineering 105 (2), 935-952 2023
Citations: 16



A review note on different components of simple electromagnetic levitation systems
S Banerjee, MK Sarkar, PK Biswas, R Bhaduri, P Sarkar
IETE Technical review 28 (3), 256-264 2011
Citations: 16



Modelling, simulation and performance comparison of different membership functions based fuzzy logic control for an active magnetic bearing system
S Gupta, PK Biswas, B Aljafari, SB Thanikanti, SK Das
The Journal of Engineering 2023 (2), e12229 2023
Citations: 15



Self-controlled PMSM drive employed in light electric vehicle-dynamic strategy and performance optimization
C Sain, PK Biswas, PR Satpathy, TS Babu, HH Alhelou
IEEE Access 9, 57967-57975 2021
Citations: 15



Performance analysis of drone sqadron optimisation based MPPT controller for grid implemented PV battery system under partially shaded conditions
D Mazumdar, PK Biswas, C Sain, F Ahmad, TS Ustun, A Kalam
Renewable Energy Focus 49, 100577 2024
Citations: 14



GAO optimized sliding mode based reconfigurable step size Pb&O MPPT controller with grid integrated EV charging station
D Mazumdar, PK Biswas, C Sain, TS Ustun
IEEE Access 12, 10608-10620 2023
Citations: 14