sudheer Hanumanthakari

@ifheindia.org

Associate professor
Faculty of Science and Technology, ICFAI Foundation for Higher Education

sudheer Hanumanthakari


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https://researchid.co/hsudheeer

RESEARCH, TEACHING, or OTHER INTERESTS

Electrical and Electronic Engineering, Artificial Intelligence, Multidisciplinary, Computer Science Applications
31

Scopus Publications

583

Scholar Citations

12

Scholar h-index

15

Scholar i10-index

Scopus Publications

  • A hybrid approach for energy management systems in grid tied microgrids using Kepler optimization algorithm and motif-based heterogeneous graph attention network
    Ashutosh Pandey, Sudheer Hanumanthakari, B. Anandaraj, Jarupula Somlal
    Energy Systems, 2026
  • An integrated LSTM-based machine learning framework for optimal charging and peak load reduction in xEV-integrated distribution systems
    Viswanatha Rao Jawalkar, Ch. Hemanth Kumar, Sudheer Hanumanthakari, K.E. Ch. Vidya Sagar N.A., Venkatakrishnamurthy Talari
    International Journal of Mathematical Modelling and Numerical Optimisation, 2026
    Inderscience is a global company, a dynamic leading independent journal publisher disseminates the latest research across the broad fields of science, engineering and technology; management, public and business administration; environment, ecological economics and sustainable development; computing, ICT and internet/web services, and related areas.
  • Automated electric power generation from agricultural resources
    Sudheer Hanumanthakari, R. Vinoth Kumar, Jeswin Arputhabalan, P. Velmurugan, Mrutyunjaya S. Yalawar
    Integrating Artificial Intelligence into the Energy Sector, 2025
    From agricultural resources, automatic generation of electric power represents the revolutionary approach towards energy production. In this chapter, the incorporation of automation technology in agricultural practices aimed at optimizing the conversion of organic waste, crop residues, and other biomass into electricity has been referred to. It places emphasis on such modern techniques as anaerobic digestion, gasification, and biomass combustion and hints at the innovations brought about by automation, which significantly enhance efficiency, reduce the costs of operations, and minimize adverse impact on the environment. Scale, system integration, and economic feasibility are considered issues as well. Monitoring and controlling of power generation systems and processes through the implementation of key technologies like sensors, control systems, and data analytics are considered.
  • Certain investigations on performance analysis of different converter designs for smart micro-grid systems
    N. Krishnamoorthy, Sudheer Hanumanthakari, Gobimohan Sivasubramanian, A. Prabha, P. Hemachandu, P. Veeramanikandan, Nageswara Rao Medikondu, R. Gopinathan, L. Anbarasu
    International Journal of Power Electronics and Drive Systems, 2025
    This paper proposes a grid-connected hybrid renewable power system. A LUO converter driven by ABC-PI controller is used to produce stable DC-link voltage. To enhance the voltage, a LUO converter is used, and the boosted voltage is regulated by an ABC-PI controller. Using the suggested optimization approach, the power fluctuation is kept at a low value. The execution of the proposed optimization is efficient, as it is simple and robust. It has a limited number of control parameters as compared to other approaches. The suggested method is described in complete detail, together with its converter and control mechanisms. The modeling and experimental results are validated to ensure that the system is feasible. The HRES is analyzed through simulation in MATLAB with converters like boost, SEPIC, and LUO. The results reveal that the LUO converter performs better with a minimum settling time of 0.175 seconds with a source current THD of 1.29%. From the modeling and the simulation results, it has been revealed that the proposed technology provides more reliable and steady power.
  • Enhancing multi-class lung disease classification in chest x-ray images: A hybrid manta-ray foraging volcano eruption algorithm boosted multilayer perceptron neural network approach
    Rajendran Thavasimuthu, Sudheer Hanumanthakari, Sridhar Sekar, Sakthivel Kirubakaran
    Network Computation in Neural Systems, 2025
    One of the most used diagnostic imaging techniques for identifying a variety of lung and bone-related conditions is the chest X-ray. Recent developments in deep learning have demonstrated several successful cases of illness diagnosis from chest X-rays. However, issues of stability and class imbalance still need to be resolved. Hence in this manuscript, multi-class lung disease classification in chest x-ray images using a hybrid manta-ray foraging volcano eruption algorithm boosted multilayer perceptron neural network approach is proposed (MPNN-Hyb-MRF-VEA). Initially, the input chest X-ray images are taken from the Covid-Chest X-ray dataset. Anisotropic diffusion Kuwahara filtering (ADKF) is used to enhance the quality of these images and lower noise. To capture significant discriminative features, the Term frequency-inverse document frequency (TF-IDF) based feature extraction method is utilized in this case. The Multilayer Perceptron Neural Network (MPNN) serves as the classification model for multi-class lung disorders classification as COVID-19, pneumonia, tuberculosis (TB), and normal. A Hybrid Manta-Ray Foraging and Volcano Eruption Algorithm (Hyb-MRF-VEA) is introduced to further optimize and fine-tune the MPNN's parameters. The Python platform is used to accurately evaluate the proposed methodology. The performance of the proposed method provides 23.21%, 12.09%, and 5.66% higher accuracy compared with existing methods like NFM, SVM, and CNN respectively.
  • Intelligent and real-time Parking System
    Sudheer Hanumanthakari
    E3s Web of Conferences, 2024
    With increased use of smart gadgets, the Internet of Things (IoT) has recently become a regular part of everyone’s daily life. Parking spaces have become a significant challenge since the majority of the population in metro cities uses private vehicles more frequently. Because of the most recent technology and the growing popularity of the concept of smart cities, the paper proposes an IoT based smart parking system. This research study focuses on making the best use of the available space, managing traffic effectively, and utilizing resources to their fullest potential. Work has been done in the previous years to improve the smart parking system, and research is still being done to create a system that is both technologically advanced and user-friendly. IoT based real time smart parking system helps the users to order and find the parking slots using Android application and Web Application is designed. The proposed model helps the public with personal vehicles to find parking spaces in specific locations.
  • Deep Learning for Energy Demand Forecasting in Electric Vehicle Charging Stations
    Sudheer Hanumanthakari, Anita S, M. Beulah Viji Christiana, Vellayan Srinivasan, Sathish Kannan, S.K. Nandha Kumar
    Proceedings 2024 5th International Conference on Mobile Computing and Sustainable Informatics Icmcsi 2024, 2024
    Electric vehicle (EV) growth in the Indian market has resulted in an enormous rise in energy demand. Because EVs are becoming more popular, effective charging infrastructure and energy management technologies are essential. Intelligent energy management systems are necessary to reduce the risks of power outages and disruptions resulting from the increasing number of EVs on the road. This paper proposes a novel Deep Learning (DL) model called Fractional Gradient-Based Recurrent Neural Network (FG-RNN) for predicting energy demand at electric vehicle charging stations (EVCS) to solve these challenges. This study examines and preprocesses data from an adaptable charging network (ACN). The proposed FG-RNN model was tested against two DL models: Deep Neural Network (DNN) and Long Short-Term Memory (LSTM). The FG-RNN model is one of the better solutions because of its high R-squared (R2) value of 97.682%. Furthermore, the model has a remarkably low Mean Absolute Percentage Error (MAPE) of 2.51% and a Mean Squared Error (MSE) of 0.072. Based on these results, the FG-RNN model appears to be a promising option for intelligent energy management systems for predicting energy consumption for EVCS.
  • A Faster and Robust Artificial Neural Network Based Image Encryption Technique With Improved SSIM
    Asisa Kumar Panigrahy, Shima Ramesh Maniyath, Mithileysh Sathiyanarayanan, Mohan Dholvan, T. Ramaswamy, Sudheer Hanumanthakari, N. Arun Vignesh, S. Kanithan, Raghunandan Swain
    IEEE Access, 2024
    A robust image encryption process is still one of the most challenging tasks in image security owing to massive degree and sensitivity nature of information in the form of pixels. The hurdles include greater computational difficulty, information loss during encryption, universality, applicability of the approach, and less scalability. Many image encryption methods existing in literature merely encrypt a portion of the data. Therefore, we propose a robust, dynamic, and sophisticated technique to enhance the encryption process to make it difficult for an attacker to gain unauthorized access to the pixel data. The proposed system uses a novel analytical research methodology through dynamically harnessing the potential of neural network that offers better forward and backward secrecy, dynamic control, and automatic management unlike any existing system. The encryption procedure comprises of two levels, first level is confusion- permutation of input image and second level is diffusion by Bit XOR operation for secure transmission and storage of images. Finally, the encrypted image is used as a target for training the Artificial Neural Network (ANN) model. ANN trained values are used for final level of encryption to develop a Neural Network (NN)-based cryptosystem, where the crypto analyst or the cracker need to know the number of adaptive iterations and the final weights for the encryption and decryption systems to crack the system which offers higher degree of resiliency towards potential threats. Results and security analysis show that our algorithm has good encryption effect, ability of resisting exhaustive attack, statistical attack, and differential attack. The system performance after implementing the proposed method is compared with existing methods present in literature with respect to processing time and Structural Similarity Index Measure (SSIM). Our proposed method offers significant reduction in encryption time and is approximately 10-15% faster than others with SSIM of 0.002165, close to zero after encryption. It also successfully balances the image quality with higher image security and lower computational complexity.
  • Analysis of GAA Junction Less NS FET Towards Analog and RF Applications at 30 nm Regime
    Asisa Kumar Panigrahy, Sudheer Hanumanthakari, Shridhar B. Devamane, Shruti Bhargava Choubey, M. Prasad, D. Somasundaram, N. Kumareshan, N. Arun Vignesh, Gnanasaravanan Subramaniam, Durga Prakash M, Raghunandan Swain
    IEEE Open Journal of Nanotechnology, 2024
    This research focuses on a quantum model created using an entirely novel nanosheet FET. The standard model describes the performance of a Gate-all-around (GAA) Junction-less (JL) nanosheet device with a gate dielectric of SiO<sub>2</sub> and HfO<sub>2</sub>, each having a thickness of 1 nm. The performance of both the classical and quantum models of the GAA nanosheet device is evaluated using the visual TCAD tool, which measures the <italic>I<sub>ON</sub></italic>, <italic>I<sub>OFF</sub></italic>, <italic>I<sub>ON</sub>/ I<sub>OFF</sub></italic>, threshold voltage, DIBL, gain parameters (g<sub>m</sub>, g<sub>d</sub>, A<sub>v</sub>), gate capacitance, and cut-off frequency (<italic>f<sub>T</sub></italic>). The device is suited for applications needing rapid switching since it has a low gate capacitance of the order of 10<sup>–18</sup>, according to the simulation results. A transconductance (g<sub>m</sub>) value of 21 µS and an impressive cut-off frequency of 9.03 GHz are displayed during device analysis. A detailed investigation has also been done into the P-type device response for the same device. Finally, the proposed GAA nanosheet device is used in the inverter model. The NSFET-based inverter, although having higher gate capacitance, has the shortest propagation latency.
  • Machine learning based crop recommendation system
    Artificial Intelligence and Knowledge Processing Methods and Applications, 2023
  • Biomining method to extract metal components using computer-printed circuit board e-waste
    Sudheer Hanumanthakari, M. D. Mohan Gift, K. V. Kanimozhi, Murapaka Dhanalakshmi Bhavani, Kalyan Devappa Bamane, Sampath Boopathi
    Handbook of Research on Safe Disposal Methods of Municipal Solid Wastes for A Sustainable Environment, 2023
  • Deep Learning based Fault Diagnosis in Electrical Machinery in Industrial Sector based on Data Mining Techniques
    Sudheer Hanumanthakari, Neha Garg, P Chandrakanth, Navdeep Dhaliwal, R Ramadevi, Siva Sankara Babu Chinka
    Proceedings of the 5th International Conference on Inventive Research in Computing Applications Icirca 2023, 2023
  • A novel and comprehensive mechanism for the energy management of a Hybrid Micro-grid System
    Farrukh Sayeed, Sudheer Hanumanthakari, Sujo Oommen, Anitha G., Hemavathi S., Aditya Kumar Singh Pundir, M. Sudhakar, Ravishankar Sathyamurthy, V. Mohanavel
    Energy Reports, 2022
  • Detecting Face Mask for Prevent COVID-19 Using Deep Learning: A Novel Approach
    Sudheer Hanumanthakari, Sandeep Kumar Panda
    Smart Innovation Systems and Technologies, 2022
  • A Technological Research on Electric Vehicles Charging Approaches and Optimization Methods
    B. Veena Vani, Dharavath Kishan, Md Waseem Ahmad, Sudheer Hanumanthakari, B. Naresh Kumar Reddy
    2022 12th IEEE Symposium on Computer Applications and Industrial Electronics Iscaie 2022, 2022
  • Metaheuristic Algorithm for Automatic Cruise Control System
    V. Prasanna, A Nelson, Sudheer Hnaumanthakari, V. Kamal Kumar, S. Kirubakaran, M Jogendra Kumar
    3rd International Conference on Smart Electronics and Communication Icosec 2022 Proceedings, 2022
  • IoT based Patients Monitoring System in Healthcare Service
    Sudheer Hanumanthakari, SVVSR Kumar Pullela, Shankar Nayak Bhukya, K. Vijayalakshmi, S Rehan Ahmad, Narendra Kumar
    International Conference on Automation Computing and Renewable Systems Icacrs 2022 Proceedings, 2022
  • Machine Learning Strategy to Achieve Maximum Energy Harvesting and Monitoring Method for Solar Photovoltaic Panel Applications
    Bibhu Prasad Ganthia, Sudheer Hanumanthakari, Hemachandra Gudimindla, Harishchander Anandaram, M. Siva Ramkumar, Monalisa Mohanty, S. Raja Gopal, Atul Sarojwal, Kibrom Menasbo Hadish
    International Journal of Photoenergy, 2022
  • Flexible Polymer Solar Cells with High Efficiency and Good Mechanical Stability
    I. Kathir, Santaji Krishna Shinde, C. Parswajinan, Sudheer Hanumanthakari, K. Loganathan, S. Madhavarao, A. H. Seikh, M. H. Siddique, Manikandan Ganesan
    International Journal of Photoenergy, 2022
  • Design and analysis of high reliable fault tolerance subsystem for micro computer systems
    Sudheer Hanumanthakari, G Sai Vishal Reddy, B. Naresh Kumar Reddy
    Iscaie 2021 IEEE 11th Symposium on Computer Applications and Industrial Electronics, 2021
  • Comparative Analysis of Different Types of Membership Functions for Fuzzy Logic Controller in Direct Torque Control of Induction Motor
    Sudheer Hanumanthakari
    Lecture Notes in Electrical Engineering, 2021
  • Enabling smart education system using blockchain technology
    A. R. Sathya, Sandeep Kumar Panda, Sudheer Hanumanthakari
    Intelligent Systems Reference Library, 2021
  • Implementaion of SVM-DTC of induction motor using FPGA
    H Sudheer, S K Fodad, B Sarvesh
    IEEE International Conference on Power Control Signals and Instrumentation Engineering Icpcsi 2017, 2018
  • Implementation of robust direct torque control of induction motor using FPGA Spartan-6 board
    Journal of Electrical Systems, 2018
  • Sensorless Direct Torque Control of Induction Motor Using Neural Network-Based Duty Ratio Controller
    H. Sudheer, S. F. Kodad, B. Sarvesh
    Lecture Notes in Electrical Engineering, 2018
  • Improvements in SVM-DTC of induction motor with fuzzy logic controllers using FPGA
    Hanumanthakari Sudheer, S. F. Kodad, B. Sarvesh
    International Review of Electrical Engineering, 2017
  • Direct Torque and Flux control of induction machine using Fuzzy Logic controller
    H Sudheer, SF Kodad, B Sarvesh
    Proceeding of IEEE 2nd International Conference on Advances in Electrical Electronics Information Communication and Bio Informatics IEEE Aeeicb 2016, 2016
  • Optimal duty ratio controller for improved DTFC of induction motor using Fuzzy logic
    Sudheer H, Kodad SF, Sarvesh B
    2016 IEEE Students Conference on Electrical Electronics and Computer Science Sceecs 2016, 2016
  • Sensorless direct torque control of induction motor using ai based duty ratio controllers
    Sudheer Hanumanthakari, S. F. Kodad, Sarvesh Botlaguduru
    International Review on Modelling and Simulations, 2016
  • Improved fuzzy logic based DTC of induction machine for wide range of speed control using AI based controllers
    Journal of Electrical Systems, 2016
  • A voltage controller in photo-voltaic system with battery storage for stand-alone applications
    Ganesh Dharmireddy, Moorthi S, Sudheer Hanumanthakari
    International Journal of Power Electronics and Drive Systems, 2012

RECENT SCHOLAR PUBLICATIONS

  • A hybrid approach for energy management systems in grid tied microgrids using Kepler optimization algorithm and motif-based heterogeneous graph attention network
    A Pandey, S Hanumanthakari, B Anandaraj, J Somlal
    Energy Systems, 1-28 , 2026
    2026
  • An integrated LSTM-based machine learning framework for optimal charging and peak load reduction in xEV-integrated distribution systems
    VR Jawalkar, CH Kumar, S Hanumanthakari, KECV Sagar, V Talari
    International Journal of Mathematical Modelling and Numerical Optimisation … , 2026
    2026
  • Enhancing multi-class lung disease classification in chest x-ray images: A hybrid manta-ray foraging volcano eruption algorithm boosted multilayer perceptron neural network …
    R Thavasimuthu, S Hanumanthakari, S Sekar, S Kirubakaran
    Network: Computation in Neural Systems 36 (3), 987-1018 , 2025
    2025
    Citations: 3
  • Certain investigations on performance analysis of different converter designs for smart micro-grid systems
    N Krishnamoorthy, S Hanumanthakari, G Sivasubramanian, A Prabha, ...
    International Journal of Power Electronics and Drive Systems (IJPEDS) 16 (1 … , 2025
    2025
  • Automated Electric Power Generation From Agricultural Resources
    S Hanumanthakari, RV Kumar, J Arputhabalan, P Velmurugan, ...
    Integrating Artificial Intelligence Into the Energy Sector, 185-210 , 2025
    2025
    Citations: 1
  • Analysis of GAA junction less NS FET towards analog and RF applications at 30 nm regime
    AK Panigrahy, S Hanumanthakari, SB Devamane, SB Choubey, ...
    IEEE Open Journal of Nanotechnology 5, 1-8 , 2024
    2024
    Citations: 22
  • Deep learning for energy demand forecasting in electric vehicle charging stations
    S Hanumanthakari, S Anita, MBV Christiana, V Srinivasan, S Kannan, ...
    2024 5th International Conference on Mobile Computing and Sustainable … , 2024
    2024
    Citations: 2
  • A faster and robust artificial neural network based image encryption technique with improved SSIM
    AK Panigrahy, SR Maniyath, M Sathiyanarayanan, M Dholvan, ...
    IEEE Access 12, 10818-10833 , 2024
    2024
    Citations: 44
  • Corrections to" A Faster and Robust Artificial Neural Network Based Image Encryption Technique With Improved SSIM"
    A Kumar Panigrahy, S Ramesh Maniyath, M Sathiyanarayanan, ...
    IEEE Access 12, 137522-137522 , 2024
    2024
  • Intelligent and real-time Parking System
    S Hanumanthakari
    E3S Web of Conferences 472, 03003 , 2024
    2024
    Citations: 1
  • Machine Learning Based Crop Recommendation System
    K Adapa, S Hanumanthakari
    Artificial Intelligence and Knowledge Processing: Methods and Applications … , 2023
    2023
  • Deep Learning based Fault Diagnosis in Electrical Machinery in Industrial Sector based on Data Mining Techniques
    S Hanumanthakari, N Garg, P Chandrakanth, N Dhaliwal, R Ramadevi, ...
    2023 5th International Conference on Inventive Research in Computing … , 2023
    2023
    Citations: 4
  • Machine Learning Based Crop Recommendation System
    KAS Hanumanthakari
    Artificial Intelligence and Knowledge Processing: Methods and Applications … , 2023
    2023
  • Biomining Method to Extract Metal Components Using Computer-Printed Circuit Board E-Waste
    S Hanumanthakari, MDM Gift, KV Kanimozhi, MD Bhavani, KD Bamane, ...
    Handbook of Research on Safe Disposal Methods of Municipal Solid Wastes for … , 2023
    2023
    Citations: 52
  • IoT based patients monitoring system in healthcare service
    S Hanumanthakari, SK Pullela, SN Bhukya, K Vijayalakshmi, SR Ahmad, ...
    2022 International Conference on Automation, Computing and Renewable Systems … , 2022
    2022
    Citations: 11
  • A novel and comprehensive mechanism for the energy management of a Hybrid Micro-grid System
    F Sayeed, S Hanumanthakari, S Oommen, AKS Pundir, M Sudhakar, ...
    Energy reports 8, 847-862 , 2022
    2022
    Citations: 32
  • Metaheuristic Algorithm for Automatic Cruise Control System
    V Prasanna, A Nelson, S Hnaumanthakari, VK Kumar, S Kirubakaran, ...
    2022 3rd International Conference on Smart Electronics and Communication … , 2022
    2022
    Citations: 1
  • Detecting face mask for prevent COVID-19 using deep learning: A novel approach
    S Hanumanthakari, SK Panda
    Smart Intelligent Computing and Applications, Volume 2: Proceedings of Fifth … , 2022
    2022
    Citations: 44
  • A technological research on electric vehicles charging approaches and optimization methods
    BV Vani, D Kishan, MW Ahmad, S Hanumanthakari, BNK Reddy
    2022 IEEE 12th Symposium on Computer Applications & Industrial Electronics … , 2022
    2022
    Citations: 6
  • AI Grounded Tumor Recognition Device Using Medical Image Processing
    sudheer Hanumanthakari
    IN Patent 14/2,022 , 2022
    2022

MOST CITED SCHOLAR PUBLICATIONS

  • Enabling smart education system using blockchain technology
    AR Sathya, SK Panda, S Hanumanthakari
    Blockchain Technology: Applications and Challenges, 169-177 , 2021
    2021
    Citations: 87
  • Improvements in direct torque control of induction motor for wide range of speed operation using fuzzy logic
    H Sudheer, SF Kodad, B Sarvesh
    Journal of Electrical Systems and Information Technology 5 (3), 813-828 , 2018
    2018
    Citations: 78
  • Biomining Method to Extract Metal Components Using Computer-Printed Circuit Board E-Waste
    S Hanumanthakari, MDM Gift, KV Kanimozhi, MD Bhavani, KD Bamane, ...
    Handbook of Research on Safe Disposal Methods of Municipal Solid Wastes for … , 2023
    2023
    Citations: 52
  • A faster and robust artificial neural network based image encryption technique with improved SSIM
    AK Panigrahy, SR Maniyath, M Sathiyanarayanan, M Dholvan, ...
    IEEE Access 12, 10818-10833 , 2024
    2024
    Citations: 44
  • Detecting face mask for prevent COVID-19 using deep learning: A novel approach
    S Hanumanthakari, SK Panda
    Smart Intelligent Computing and Applications, Volume 2: Proceedings of Fifth … , 2022
    2022
    Citations: 44
  • A voltage controller in photo-voltaic system with battery storage for stand-alone applications
    D Ganesh, S Moorthi, H Sudheer, D Ganesh, S Moorthi, H Sudheer
    International Journal of Power Electronics and Drive System (IJPEDS) 2 (1), 9-18 , 2012
    2012
    Citations: 35
  • A novel and comprehensive mechanism for the energy management of a Hybrid Micro-grid System
    F Sayeed, S Hanumanthakari, S Oommen, AKS Pundir, M Sudhakar, ...
    Energy reports 8, 847-862 , 2022
    2022
    Citations: 32
  • Regular paper Improved Fuzzy Logic based DTC of Induction machine for wide range of speed control using AI based controllers
    H Sudheer, SF Kodad, B Sarvesh
    J. Electr. Syst 12 (2), 301-314 , 2016
    2016
    Citations: 32
  • Analysis of GAA junction less NS FET towards analog and RF applications at 30 nm regime
    AK Panigrahy, S Hanumanthakari, SB Devamane, SB Choubey, ...
    IEEE Open Journal of Nanotechnology 5, 1-8 , 2024
    2024
    Citations: 22
  • Machine learning strategy to achieve maximum energy harvesting and monitoring method for solar photovoltaic panel applications
    BP Ganthia, S Hanumanthakari, H Gudimindla, H Anandaram, ...
    International Journal of Photoenergy 2022 (1), 4493116 , 2022
    2022
    Citations: 21
  • Direct Torque and Flux control of Induction Machine using Fuzzy Logic controller
    H Sudheer, SF Kodad, B Sarvesh
    Journal of Electrical Engineering, ISSN: 1582:4594 17 (2), 122-129 , 2017
    2017
    Citations: 20
  • Comparative analysis of different types of membership functions for fuzzy logic controller in direct torque control of induction motor
    S Hanumanthakari
    Intelligent Computing in Control and Communication: Proceeding of the First … , 2021
    2021
    Citations: 12
  • Sensorless Direct Torque Control of Induction Motor Using AI Based Duty Ratio Controllers
    SB Sudheer Hanumanthakari, S. F. Kodad
    International Review on Modeling and Simulations 9 (5), 339-347 , 2016
    2016
    Citations: 12
  • IoT based patients monitoring system in healthcare service
    S Hanumanthakari, SK Pullela, SN Bhukya, K Vijayalakshmi, SR Ahmad, ...
    2022 International Conference on Automation, Computing and Renewable Systems … , 2022
    2022
    Citations: 11
  • Torque ripple reduction in direct torque control of induction motor using fuzzy logic based duty ratio controller
    H Sudheer, SF Kodad, B Sarvesh
    International Journal of Electronic Engineering Research 3 (1), 1-12 , 2011
    2011
    Citations: 10
  • Improved sensorless direct torque control of induction motor using fuzzy logic and neural network based duty ratio controller
    I IJ-AI
    IAES International Journal of Artificial Intelligence (IJ-AI) , 2017
    2017
    Citations: 9
  • Optimal duty ratio controller for improved DTFC of induction motor using fuzzy logic
    H Sudheer, SF Kodad, B Sarvesh
    2016 IEEE Students' Conference on Electrical, Electronics and Computer … , 2016
    2016
    Citations: 9
  • Improved direct torque control of induction motor using fuzzy logic based duty ratio controller
    H Sudheer, SF Kodad, B Sarvesh
    International Journal of Advances in Engineering & Technology 1 (5), 473 , 2011
    2011
    Citations: 9
  • Implementaion of SVM-DTC of induction motor using FPGA
    H Sudheer, SK Fodad, B Sarvesh
    2017 IEEE International Conference on Power, Control, Signals and … , 2017
    2017
    Citations: 7
  • A technological research on electric vehicles charging approaches and optimization methods
    BV Vani, D Kishan, MW Ahmad, S Hanumanthakari, BNK Reddy
    2022 IEEE 12th Symposium on Computer Applications & Industrial Electronics … , 2022
    2022
    Citations: 6