Quadruple spherical tank systems with automatic level control applications using fuzzy deep neural sliding mode FOPID controller Ashwini A, S.R. Sriram, Joel livin A Journal of Engineering Research Kuwait, 2025 The premier goal of this research is to develop the Fuzzy Deep Neural Sliding Mode Fractional Order Proportional Integral Derivative (FDN-SM-FOPID) controller system for controlling liquid in quadruple spherical tank systems. This is used in non-linear spherical systems to control the level of liquid in real time. These models' dynamics allow for a more accurate identification of the spherical tank system that generates control signals from liquid samples obtained at reference levels. However, because the system is susceptible to outside disturbances, error minimization is not done. Therefore, it requires the addition of a special controller to lessen this flaw. The suggested Deep Neural Fuzzy model's six-layered network is optimized using the back-propagation method. As a result, the system's efficient training reduces offset model errors, steady state errors, and unmeasured disturbances. The liquid level is maintained and controlled by this neural intelligence system, which meets the necessary design requirements such as no overshoot, time constant, less settling and rise time, which is used in various platforms. The FOMCON toolbox in MATLAB software is used for research simulation work. The chemical industry, wastewater treatment, the aerospace industry, and the pharmaceutical industry have all employed the suggested quadruple spherical tank system to test its practicality. The experimental and simulation results are demonstrated by a real-time liquid control experimental setup.
Design and Performance Optimization of Lead-Free FASnI3 Perovskite Solar Cells Using SCAPS-1D S Nivedita, S R Sriram 7th IEEE International Conference on Emerging Electronics Icee 2025, 2025 Perovskite solar cells (PSCs) have emerged as one of the most promising next-generation photovoltaic technologies due to their rapidly rising power conversion efficiencies, low-cost processing, and tunable optoelectronic properties. While lead-based perovskites have achieved efficiencies exceeding 25%, their toxicity raises serious environmental and health concerns. Tin-based perovskites have been explored as non-toxic alternatives, with formamidinium tin iodide (FASnI<inf xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">3</inf>) exhibiting excellent optoelectronic properties and a suitable bandgap for single-junction solar cells. However, device instability caused by the oxidation of Sn<sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2+</sup> to Sn<sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">⁴⁺</sup> continues to limit their performance. In this work, a lead-free FASnI<inf xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">3</inf>-based perovskite solar cell is designed and simulated using SCAPS-1D. Tin fluoride (SnF<inf xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</inf>) was incorporated as an additive to suppress Sn<sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2+</sup> oxidation and to improve film quality. Cuprous iodide (CuI) was used as a low-cost hole-transport material instead of Spiro-OMeTAD. Simulation results indicate that the proposed device structure achieves improved efficiency, open-circuit voltage (V<inf xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">oc</inf>), and short-circuit current density (J<inf xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">sc</inf>). This work highlights the potential of environmentally friendly tin-based perovskites as a promising alternative to lead-based perovskite solar cells.
Farming 4.0: Cultivating the Future with Internet of Things Empowered on Smart Agriculture Solutions A. Ashwini, S.R. Sriram, J. Manoj Prabhakar, Seifedine Kadry Networked Sensing Systems, 2025 Agriculture is one of the major sectors that have been considered to be essential to ensuring food security. The world's population is growing, and there are many natural factors that make nourishing billions of people challenging. The application of Internet of Things (IoT) in agriculture is revolutionizing the field and creating opportunities for accurate monitoring and data-driven farming. The Internet of Things with the sensors and unmanned aircraft, which helps in tracking the farming lands based on the phenomenon of humidity, crop performance, livestock, and temperature are termed as Farming 4.0. This research chapter holds the smart agriculture concept that highlights the usage of Internet of Things in its evolutionary concept. This nominally increases the food output, as the year 2050 is predicted to have food shortage due to growing population, traditional farming methods, and outdated skills of farmers in field pattern. This fine goal has led to the enlarged connectivity between the digital scale of the marketed items using the internet. The loss reduction with increase in yield values is determined by the process of gathering data continuously with a precise level of monitoring. By considering the periodic data with the current trends, the farmers predict the yield with the disease outbreaks enhancing the consumer preferences with accurate data-driven methods. Making decisions based on strategic values helps in choosing the best strategic plan. Managing the strategies in remote locations using the IoT helps in providing the data with real-time access creating web alerts responding to disease outbreak with a high range of accuracy at nominal consumer preferences. This is made possible by connecting the sensors to the land. This helps in monitoring the storage conditions optimizing the tracking of shipments on agricultural supply chain values. This ensures producing high- quality food with waste reduction enhancing the efficiency of the supply chain process. The data gathered using the IoT based on artificial intelligence and various training procedures help the supporting system with decisions packed, thus highlighting suggestions and various insights. The agro-based sensor devices used for evaluation are connected to farming, service types, and the readiness of actual technological levels chosen for practicing. The results are framed with the process of investigating the technologies at the digital level such as machine learning embedded on the robotic systems and the Internet of Things. Thus, embracing security with IoT protocols helps to protect the assets on the farmland fostering long-term technological viability. Thus, the future of agriculture lies in leveraging the global IoT, which helps in achieving improved choices and accurate level of monitoring with suitable practices.
Artificial intelligence's impact on thrust manufacturing with innovations and advancements in aerospace A. Ashwini, S. R. Sriram, A. Manisha, J. Manoj Prabhakar Industry Applications of Thrust Manufacturing Convergence with Real Time Data and AI, 2024 Artificial intelligence (AI) has emerged as a transformative force in the area of thrust production. The substantial effects of AI-powered tools on the production of engines, turbine systems, and propulsion that create lift for aircraft are examined in this chapter. Green aviation is advancing due to electric hybrid engine technology, which reduces emissions and solve environmental issues. Artificial intelligence, additive manufacturing, and technological innovation are shaping its evolution. This chapter explores developments and emerging themes offering an overview of the opportunities facing the aerospace sector. Software for process optimization examines data in real time to find bottlenecks and boost output effectiveness. Design optimization is aided by AI-driven models, while operational safety and fuel efficiency are enhanced by performance monitoring systems. These developments bring in a new age of technological growth and excellence by highlighting the crucial role that AI plays in enhancing reliability, productivity, and safety of thrust manufacturing.
Smart Farming Based Early Classification of Paddy Blast Disease Using Adaptive Deep Learning Algorithm Ashwini A, G Preemi, S. R. Sriram, D Ferlin Deva Shahila, M Angel Merlin Suji, Duvvuru Venkata Sai Sudeep Reddy Proceedings of International Conference on Circuit Power and Computing Technologies Iccpct 2024, 2024 The backbone of the Indian economy, agriculture is essential to Indians' standard way of life. Plant disease monitoring by hand typically involves a tremendous labor and takes more time to perform. The primary goal of this research is to help farmers, particularly those who are dealing with blast disease in rice crops, by quickly and reliably detecting plant diseases. The primary goal of the research is to catalog the diseases that affect rice and identify crop infections early on. Therefore, the development of soft computing and image processing technologies for smart agriculture applications is the subject of this research study, with a special emphasis on applications in innovative design for the detection of diseases in rice. The key methods of analysis used include preprocessing, classification, feature extraction, and picture acquisition. The lands used for agriculture are the source of input images. Dmey wavelet filtering is the first step in the pre-processing procedure which removes noise from images. Next, image-based crop feature extraction techniques are utilized to perform an extensive study. The proposal is to use the Adaptive deep neural network (ADNN) to address the overlapping issue. In ADNN, the total accuracy is 97.3%. A wide range of rice blast diseases are correctly identified with the desired accuracy, regardless of the obscured settings, according to the evaluation results of the suggested method.
A physics-based model for LER-induced threshold voltage variations in double-gate MOSFET S. R. Sriram, B. Bindu Journal of Computational Electronics, 2020 The line-edge roughness (LER) has become one of the dominant sources of process variations in multi-gate transistors. The estimation of threshold voltage distribution due to LER through atomistic simulations is computationally intensive, even though these simulations provide accurate results. In this paper, a physics-based model for channel LER-induced threshold voltage fluctuations due to variations of the silicon-body thickness in a double-gate (DG) MOSFET is presented. The developed $$V_\\mathrm{TH}$$ V TH model gives more insights into the dependence of device and LER parameters on the $$V_\\mathrm{TH}$$ V TH variations with a reduced computational time. The computed $$V_\\mathrm{TH}$$ V TH variations due to different LER patterns are validated with TCAD simulations. The threshold voltage standard deviation due to LER in 500 device samples for different device dimensions, doping concentration and biases is studied. The developed model can be easily integrated in any circuit simulator to predict the threshold voltage variations of the devices due to LER.
An Analytical Model of Single-Event Transients in Double-Gate MOSFET for Circuit Simulation Y. M. Aneesh, S. R. Sriram, K. R. Pasupathy, B. Bindu IEEE Transactions on Electron Devices, 2019 In this paper, a physics-based bias-dependent model of single-event transients (SETs) in double-gate (DG) MOSFET suitable for circuit simulation is presented. The existing approaches that use double exponential and dual double-exponential current sources to emulate these transient currents in the circuit simulators depend on the parameters extracted from TCAD device simulations. In order to capture the essential physics behind these current transients in the circuit simulations, there is a need for a physics-based bias-dependent SET current model that considers the electrostatics in the chosen device. The proposed SET current model is developed from the solution of 2-D Poisson’s equation with proper boundary conditions of DG MOSFET. It takes into account the dependence of the transient potential and drain current on linear energy transfer (LET), strike positions, drain and gate biases, device dimensions, and channel doping. The results from the model are validated with the simulation results from TCAD. The SET current model is integrated in Cadence circuit simulator and observed through simulations the voltage perturbation at the output of the CMOS inverter due to heavy ion strike on nMOS transistor in OFF state for different LETs and loads. The proposed model captures the current plateau region effect in CMOS inverter.
Analytical modeling of random discrete traps induced threshold voltage fluctuations in double-gate MOSFET with HfO2/SiO2 gate dielectric stack Sriram S.R., Bindu B. Microelectronics Reliability, 2019 An analytical model of threshold voltage fluctuations due to random discrete traps at Si/SiO2 interface and in gate oxide regions for undoped double-gate (DG) MOSFET with high-k/SiO2 gate dielectric stack is presented in this paper. The model is derived based on the solution of 2-D Poisson's equation considering both position and number fluctuation of traps. The distribution of traps at the Si/SiO2 interfaces and in both gate oxide regions in double-gate structure are obtained using the bivariate Poisson distribution. The impact of interface and oxide traps over the threshold voltage are analyzed separately and together for the samples of 500 devices. The results from the model are verified using 2-D TCAD simulation results for different trap position, trap density, device dimension and drain bias. Even though the variability due to traps present in the gate oxide is comparatively lesser than the interface traps, the effect of oxide traps located in the interfacial layer (SiO2) cannot be neglected. The device variability increases with the consideration of both interface and oxide traps simultaneously and the threshold voltage fluctuations (ΔVTH) reach maximum of 90 mV. The proposed model takes less computational time for the calculation of threshold voltage fluctuations due to discrete traps compared to the atomistic simulations and thus it is suitable for circuit simulation.
Design of FinFET based frequency synthesizer Sobhana Tayenjam, S. R. Sriram, B. Bindu 12th IEEE International Conference Electronics Energy Environment Communication Computer Control E3 C3 Indicon 2015, 2016
