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2023 International Conference on Power, instrumentation, Energy and control, PIECON 2023

作者： Beg, Mirza Tabish Shah Rana, K.P.S. Kumar, Vineet Netaji Subhas University of Technology Department of Instrumentation and Control Engineering New Delhi India

ISBN: (纸本)9798350399769

The paper deals with an Alternate-Odd-Even (AOE) static reconfiguration technique for the power enhancement and performance improvement of the solar photovoltaic (SPV) array under partial shading conditions (PSC). The modules of the chosen 4×4 SPV array are connected electrically in a total-cross-tied (TCT) but repositioned in the SPV array using the proposed AOE reconfiguration technique. The proposed scheme is analyzed and compared with the primary 4×4 SPV array topologies, namely the total-cross-tied (TCT), honeycomb (HC), bridge-link (BL), and series-parallel (SP) for the performance analysis. This technique leads to the redistribution of shade throughout the SPV array. Due to the lower current and voltage outputs, the simple series and parallel configurations have not been considered for this analysis. The proposed technique gives an enhanced performance of the SPV array in terms of higher peak power, lower losses due to shading, improved fill factor and execution ratio, and smooth output characteristics. The proposed technique allows the researchers to design a less complex controller for tracking peak power for the SPV array under PSCs. © 2023 IEEE.

关键词： Solar power generation

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Image Forgery Detection using ELA and CNN 2

Image Forgery Detection using ELA and CNN

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2nd IEEE International Conference on Futuristic Technologies, INCOFT 2023

作者： Patankar, Sanika Joshi, Ashutosh Durge, Gaurav Jaid, Atharva Kalambe, Khomesh Dhale, Hrishikesh Vishwakarma Institute of Technology Department of Instrumentation and Control Engineering Maharashtra Pune411037 India

ISBN: (纸本)9798350308846

Picture tampering has recently increased due to the increasing popularity of photo-editing software, making it difficult to determine the authenticity of an image with the naked eye. To address this issue, we proposed a model that detects image forgeries using ELA (Error Level Analysis) and CNN (Convolutional Neural Network) techniques. ELA is a forensic tool that examines variations in compression levels, whereas CNN is a deep learning technique that can learn and extract features from photos to categorize them as either modified or legitimate. The model combines both techniques and was tested on the publicly available CASIA 2.0 dataset. According to the results, the proposed model outperforms existing deep learning models in terms of training time and computational efficiency, achieving an overall accuracy of more than 95.19%. The proposed method is an effective and efficient method for detecting a wide range of image editing techniques used for image manipulation. © 2023 IEEE.

关键词： CNN Deep Learning ELA Image Forgery Detection Image Tampering

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Optimized Multi-model Machine Learning Approach for Residential Load Prediction 5

Optimized Multi-model Machine Learning Approach for Resident...

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5th International Conference on Energy, Power, and Environment, ICEPE 2023

作者： Tomar, Anuradha Netaji Subhas University of Technology Department of Instrumentation & Control Engineering Delhi78 India

ISBN: (纸本)9798350313123

Accurate prediction of the residential load is important to increase the utilization of available local energy resources, to address over/under voltage problems, and overloading issues in low voltage (LV) distribution grids. The need for an optimized prediction model has been observed that performs well even when the dataset has characteristic deviations. This paper aims to present an optimized model for residential electrical load prediction. Linear regression, regression tree, ensemble, and gaussian process regression (GPR) methods are considered, and based on the error metrics evaluation, a prediction model with minimum error is selected for load prediction. Calendar and weather-based features are selected based on the principal component analysis. A case study has been performed, considering the measured smart meter data from a multi-storied residential house in Houston, Texas, USA. A comparison of predicted and measured residential electrical load shows that the suggested approach performs satisfactorily. © 2023 IEEE.

关键词： Energy resources

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Identification of batch reactor process using Extreme Learning Machine based Hammerstein and Hammerstein-Wiener Models

Identification of batch reactor process using Extreme Learni...

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2024 International Conference on Thermofluids and Manufacturing Science, ICTMS 2024

作者： Balakrishnan, Murugan Rajendran, Vinodha Prajwal, Shettigar J. Indiran, Thirunavukkarasu Department of Electronics and Instrumentation Engineering Annamalai University Annamalai Nagar Tamilnadu India Department of Instrumentation and Control Engineering Institution Manipal Institute of Technology Manipal Academy of Higher Education Karnataka Manipal India

This paper concentrates on system identification using neural networks, specifically avoiding the need for gradient calculation. In our proposed approach, the parameters of the nonlinear static blocks in both Hammerstein and Hammerstein-Wiener models are represented as Single Hidden Layer Feed forward Networks (SLFNs). The identification of both nonlinear and linear parameters is accomplished through the application of Extreme Learning Machine (ELM). In ELM, the hidden layer weights and biases are generated randomly and remain fixed, whereas the output weights are computed using linear regression. The training process involves a forward pass, in which the hidden layer activations are computed, followed by the computation of the output weights and backward pass is exempted, where iterative optimization based weight updates are done. To show the efficacy of the ELM based block oriented models, intense nonlinear batch reactor process is identified with its input output data. One can take away the best model fit for controller design from this ELM based modelling. © Published under licence by IOP Publishing Ltd.

关键词： Batch data processing

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Investigations on Jamming and Black Hole Attacks in Wireless Sensor Networks: An Industrial Case Study

Investigations on Jamming and Black Hole Attacks in Wireless...

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International Conference on 6G Communications Networking and Signal processing, SGCNSP 2023

作者： Lavanya, A. Udhayakumar, P. Rajkumar, K. Revathi, S. Department of Electrical and Electronics Engineering National Institute of Technology Puducherry Karaikal609609 India Department of Engineering Karaikal Port India Department of Instrumentation and Control Engineering National Institute of Technology Trichy Tiruchirappalli620015 India

ISBN: (纸本)9789819778751

As industries rapidly advance towards Industry 4.0 and the Industrial Internet of Things (IIoT), the integration of automation and digitalization has brought unprecedented efficiency gains to various sectors. Among the critical components of Industry 4.0, belt conveyors play a pivotal role in streamlining material handling processes. Many crucial parameters in the Industrial Conveyor system require constant attention and monitoring. However, this integration of digital systems also exposes these conveyor systems to new vulnerabilities, notably cyber-attacks. This paper, investigate the potential impacts of availability attack on Industrial Conveyor system. The study employs a multi-faceted approach, combining cyber-physical experiments and simulations. Black holes and jamming attacks are considered, targeting the Wireless Sensor Network (WSN) of the Industrial conveyor system. The effects of these attacks on conveyor movement, material flow, and overall production are meticulously examined. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Jamming

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Observer-based stabilization for discrete nonlinear semi-Markov jump singularly perturbed models with mode-switching delay

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Science China(Information Sciences) 2025年第4期68卷 389-390页

作者： Wenhai QI Runkun LI Ju H.PARK Zheng-Guang WU Huaicheng YAN School of Engineering Qufu Normal University Department of Electrical Engineering Yeungnam University Institute of Cyber-Systems and Control Zhejiang University Key Laboratory of Smart Manufacturing in Energy Chemical Process of Ministry of Education East China University of Science and Technology

Semi-Markov jump systems(S-MJMs) not only characterize hybrid systems but also address the limitations of Markov jump systems(MJMs) [1–3]. Due to their ability to exhibit multi-time-scale features, singularly perturbed models(SPMs) effectively model practical systems influenced by multiple time-scale phenomena [4]. In this study, the observer-based output feedback controller is asynchronous with the original system due to the time delay in the controller mode switching. A nonlinear plant with singularly perturbed parameters(SPPs) is represented using an interval type-2(IT2) fuzzy model [5].

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Analysis of Bifacial Photovoltaic Panel Under Different Reflective Surfaces 3

Analysis of Bifacial Photovoltaic Panel Under Different Refl...

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3rd IEEE International Conference on Power Electronics, Intelligent control and Energy Systems, ICPEICES 2024

作者： Kathuria, Harit Singh, Ikjot Gupta, Aditya Puniya, Gaurav Kumar, Bhavnesh Netaji Subhas University of Technology Instrumentation and Control Engineering Department Sector-3 New Delhi Dwarka110078 India

ISBN: (纸本)9798350387193

With developments in bifacial solar panels, the solar photovoltaics interest has started shifting from monofacial designs to bifacial solar panels. This paper analyses and compares the performance between a bifacial and a monofacial solar panel system. The bifacial design offers different performance characteristics based on the reflective properties of the base material. This paper reviews and compares the system's performance on various reflective surfaces. This study employs a comparative outlook on performance measures such as current, voltage, power and thermal outputs. Taking the global energy crisis into consideration, solar panels prove to be an important replacement for the conventional ways of electricity generation and bifacial solar panels improve the efficiency of a conventional solar panel. Therefore, this study is anticipated to serve as a guide for integrating bifacial photovoltaic systems in general use, increase its efficiency and also promote research in this domain. © 2024 IEEE.

关键词： Bifacial Gain Bifacial Solar Panels Monofacial Solar Panels Photovoltaic System Reflector

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Hippopotamus Optimization Based PID controller Design for LFC of Microgrid Under Cyber and Time Delay Attack 4

Hippopotamus Optimization Based PID Controller Design for LF...

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4th IEEE International Conference on Sustainable Energy and Future Electric Transportation, SEFET 2024

作者： Altaf, Aatif Kumar, Mahendra Biswas, Deblina Dr B R Ambedkar National Institute of Technology Jalandhar Department of Instrumentation and Control Engineering Punjab Jalandhar India

ISBN: (纸本)9798350383997

This paper proposes Hippopotamus Optimization (HO) based PID controller design for load frequency control (LFC) of microgrid under cyber and time delay Attack. With increasing demand for energy due to limited conventional sources and population growth has led to the restructuring of current electricity grid to incorporate renewable energy sources (RES). However, RESs irregularities pose significant technical barriers for stable, and reliable microgrid (MG) operation. These irregularities cause deviation in system frequency. To maintain system frequency at a pre-specified value, a load frequency controller is required. In today's power systems, communication networks play a crucial role, but they also pose a risk of cyberattacks. A new optimization algorithm called Hippopotamus Optimization algorithm (HOA) has emerged, inspired by nature, offering advantages in global optimization and requiring lesser design parameters. The proposed approach will be used to address challenges such as parametric uncertainty (PU), cyber and time delay attacks, and random load demand. Simulation studies have been demonstrated under different practical scenarios. © 2024 IEEE.

关键词： Three term control systems

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A**: A bidirectional approach based on analytical treatment to conventional A* for the smooth and fast trajectory planning

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International Journal of Information technology (Singapore) 2023年第4期15卷 2173-2185页

作者： Singh, Raj Kumar Nagla, K.S. Instrumentation and Control Engineering Department Dr B.R. Ambedkar National Institute of Technology Jalandhar India

Path optimization is a crucial problem in unmanned vehicles. A* algorithm is one of the conventional and reliable path planning algorithms;however, during experimental analysis, it is observed that the path selected by the algorithm is not optimal because the selected trajectory contains a high number of sharp turns with time lag. These sharp turns put a significant delay in the mobile robot’s navigation to reach the destination. Because of these sharp heading angles, the mobile robot must adjust for the optical trajectory tracking. A** based on the experimental investigation of conventional A* technique is proposed that always selects the shortest path with a smooth trajectory to reach the destination. The algorithm proposed in this research not only recommends the shortest path to reach the destination, but it also selects the trajectory having least sharp turns that resulted in timed navigation of an unmanned vehicle. With the implementation of proposed A** algorithms in real world experiment, the sharp turn in the trajectory is reduced to 13.25% with respect to conventional A*, which resulted in increasing the acceleration of mobile robot by 5.7% (cm/sec²) and the mobile robot take 15.1 s lesser time to reach the destination. This technique is quite applicable for various mobile robot applications such as path planning/shortest path selection, autonomous navigation, trajectory planning, etc. © 2023, The Author(s), under exclusive licence to Bharati Vidyapeeth's Institute of Computer Applications and Management.

关键词： Mobile robot Path planning Robotics Sensors Smooth and fast trajectory planning

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Passive UHF RFID-based sensor: Influence of electrical conductivity and localized surface cracks on industrial-grade metal specimens

Passive UHF RFID-based sensor: Influence of electrical condu...

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2024 IEEE Microwaves, Antennas, and Propagation Conference, MAPCON 2024

作者： Suresh, Setti Chakaravarthi, Geetha Applied Electromagnetics Laboratory Department of Instrumentation and Control Engineering National Institute of Technology Tamil Nadu Tiruchirappalli620015 India

ISBN: (纸本)9798350379693

Early detection and localization of initial-phase surface cracks on metal structures is critical, as they can propagate and severely compromise the structural integrity of bridges, pipelines, rail, and aerospace structures. This paper presents the study of a passive wireless RFID-based crack sensor for in-situ surface crack detection on industrial-grade metal specimens of varying conductivity. A circular-shaped, symmetrical microstrip antenna-based RFID crack sensor was designed in the Ansys HFSS tool operating in the UHF region. Simulation analysis was performed for varying surface crack depths and widths in millimeter resolution for the most commonly used Aluminum Alloy 6061 and Hot-Rolled Steel 1084 grade metal specimen. It is observed that the sensor resonant frequency variation is different for varying crack depths and widths and also for varying metal specimen grades. Preliminary no-crack measurement results illustrate that the sensor RSSI and Phase change values are sensitive with respect to changes in metal specimen conductivity. It is observed that upon calibration, the sensor crack detection capability can be leveraged to diverse industrial-grade metal specimens. © 2024 IEEE.

关键词： Hot rolling

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