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Articles 1531 - 1560 of 18077
Full-Text Articles in Entire DC Network
Estimating Stimulated Raman Scattering Noise In Cwdm O-Band Channels Induced By Two Classical Dwdm Sources In A Quantum Network Fiber Segment, Kurt T. Spranger Ii
Estimating Stimulated Raman Scattering Noise In Cwdm O-Band Channels Induced By Two Classical Dwdm Sources In A Quantum Network Fiber Segment, Kurt T. Spranger Ii
Theses and Dissertations
The purpose of this research is to estimate the stimulated Raman scattering noise induced in CWDM O-band channels by two DWDM classical sources in a terrestrial quantum optical network containing classical and quantum optical signal coexistence in the same fiber segment. A use case is defined and analyzed which extracts a single fiber segment from a notional Bell state measurement found in a notional terrestrial quantum network. A stimulated Raman scattering noise model is employed in a Python simulation to estimate and rank-order the five O-band channels with the least amount of relative induced stimulated Raman scattering noise when given …
Accelerating Homomorphic Encryption In Risc-V Architectures With Hardware Based Number Theory Transform, Zachary Legg
Accelerating Homomorphic Encryption In Risc-V Architectures With Hardware Based Number Theory Transform, Zachary Legg
Theses and Dissertations
Fully Homomorphic Encryption is an encryption paradigm enabling computations on encrypted data without the need for decryption. Such behavior is promising for securing DoD cloud computing but is also computationally demanding. To alleviate some of the computational load and accelerate FHE schemes, this research proposes adding a hardware accelerator, for the Number Theory Transform (NTT) operation, to a RISC-V processor. Thus enhancing FHE capabilities for potentially resource-constrained devices.
Generalized Characterization Of Biaxial Media Using Ultra-Wideband Multi-Static Focused Beam System With Polarimetric Calibration, Jeffrey P. Massman
Generalized Characterization Of Biaxial Media Using Ultra-Wideband Multi-Static Focused Beam System With Polarimetric Calibration, Jeffrey P. Massman
Theses and Dissertations
Novel metamaterial and metasurface realizations provide unique control of the electromagnetic wave dispersion but present many challenges for accurate constitutive parameter extraction. One measurement approach commonly employed is a freespace non-destructive focus beam system. Modern implementations are configured with multi-static dual-polarized capabilities for characterizing complex materials and offer many advantages by enabling ultra-wideband sampling, multiple measurement degrees of freedom and larger sample sizes. Practical electromagnetic material characterization of complex bianisotropic media requires the advancement of wave propagation analysis and calibration schemes. This research focuses on generalized biaxial media characterization and multi-static focused beam system metrology with polarimetric calibration schemes and …
Assessing The Relationship Between The Quasi-Biennial Oscillation And D-Region Electron Density, Natalie R. Wirth
Assessing The Relationship Between The Quasi-Biennial Oscillation And D-Region Electron Density, Natalie R. Wirth
Theses and Dissertations
High frequency (HF) communication is a vital aspect of military communication and is highly reliant upon ionospheric conditions. The variation in electron density within the lowest echelon of the ionosphere, the D-region, can significantly impact HF signals, making communication inconsistent and unreliable for these wavelengths. Despite the D-region’s important, research in this area mainly focuses on understanding the impact of space weather anomalies on the upper ionosphere, particularly its higher layers, with relatively little exploration of the D-region. This region, situated closest to the troposphere and stratosphere, has been definitively linked to solar weather events like solar flares and geomagnetic …
Identification Of Faults In Highways Using Approximation Methods And Algorithms, Khudayberdiyev Khakkulmirzayevich Mirzaakbar, Anvar Asatilloyevich Ravshanov
Identification Of Faults In Highways Using Approximation Methods And Algorithms, Khudayberdiyev Khakkulmirzayevich Mirzaakbar, Anvar Asatilloyevich Ravshanov
Chemical Technology, Control and Management
Many fast Fourier transforms are used to identify defective parts of uneven surfaces on roads and send information to relevant organizations on the road, using the " RAVON YO‘LLAR" application installed on a mobile device during car movement. We determine the uneven parts of the road. Smooth and well-maintained roads reduce the risk of vehicle collisions, skidding and other road-related incidents. Timely measures contribute to overall safety, comfort and economic efficiency.
Development Of A Mathematical Model Of Magnetic Field Distribution In Magnetic Conductors Of A Wide-Range Current Transformer, Abdurauf Safarov
Development Of A Mathematical Model Of Magnetic Field Distribution In Magnetic Conductors Of A Wide-Range Current Transformer, Abdurauf Safarov
Chemical Technology, Control and Management
The article is devoted to the analysis of the distribution of the magnetic field in the magnetic conductors of a wide-range current transformer for the development of a mathematical model that can be used as the basis for calculating its static characteristics and error. The design, replacement circuits and design model of a current transformer are given. The relations of magnetic induction and tension from the coordinate of the position of the primary winding are obtained. It is shown that the conversion range can be adjusted depending on the different positions of the bus with current, as a result of …
Strategy For Predictive Control Of The Rectification Process Based On A Model Controller With A Given Forecast, Ildar Rafkatovich Sultanov
Strategy For Predictive Control Of The Rectification Process Based On A Model Controller With A Given Forecast, Ildar Rafkatovich Sultanov
Chemical Technology, Control and Management
A method is being developed to optimize the generated controls for the multicomponent distillation process with prediction, based on predictive data with a moving horizon. The difference between this method and the classical modeling approach, in which the percentage of the degree of opening of valves installed on the output streams of the column is used as control actions, is that control occurs on the feedback principle. The proposed method is based on the use of a dynamic process model to optimize control actions in real time in order to achieve certain production targets. The essence of the MPC approach …
A Neural Network Model For Monitoring And Forecasting The Process Of Storing Oilseeds, N.A. Kabulov
A Neural Network Model For Monitoring And Forecasting The Process Of Storing Oilseeds, N.A. Kabulov
Chemical Technology, Control and Management
The paper presents the results of research on the control, forecasting and management of the storage process of oilseeds. Vegetable oil production and energy consumption are two important factors of oilseed storage systems. The first ones should meet the needs of the population quantitatively and qualitatively. As a result, in order to properly control these two important aspects, it is necessary to maintain an appropriate microclimatic environment using a computational decision support system (DSS) that is able to adapt to changes in environmental characteristics. The multilayer perceptron neural network (MLP-NN) was developed to simulate the temperature and relative humidity profiles …
Development Of A Criterion Assessing The Level Of Relationship Of Multiple Identified Characteristics For Classification, Mirzoyan Mirzaaxmedovich Kamilov, Oybek Zokirovich Koraboshev, Bobomurod Mamitjonovich Tojiboev
Development Of A Criterion Assessing The Level Of Relationship Of Multiple Identified Characteristics For Classification, Mirzoyan Mirzaaxmedovich Kamilov, Oybek Zokirovich Koraboshev, Bobomurod Mamitjonovich Tojiboev
Chemical Technology, Control and Management
This article discusses an optimized version of the standard design developed by Yu.I.Zhuravlev, an optimization procedure through an algebraic approach based on precedent algorithms that solves the problem of pattern identification. The formation of the convex hull of the recognition operator and corrective procedures of information models by mutual compensation of each other was also studied. In addition, the functional connection of recognition operators and the definition of idempotent connection of operators are analyzed.
Joint Time-Frequency Analysis: Taking Charge Penetration Depth And Current Spatial Distribution In The Single Pore As An Example, Nan Wang, Qiu-An Huang, Wei-Heng Li, Yu-Xuan Bai, Jiu-Jun Zhang
Joint Time-Frequency Analysis: Taking Charge Penetration Depth And Current Spatial Distribution In The Single Pore As An Example, Nan Wang, Qiu-An Huang, Wei-Heng Li, Yu-Xuan Bai, Jiu-Jun Zhang
Journal of Electrochemistry
In recent years, joint time-frequency analysis has once again become a research hotspot. Supercapacitors have high power density and long service life, however, in order to balance between power density and energy density, two key factors need to be considered: (i) the specific surface area of the porous matrix; (ii) the electrolyte accessibility to the intra-pore space of porous carbon matrix. Electrochemical impedance spectra are extensively used to investigate charge penetration ratio and charge storage mechanism in the porous electrode for capacitance energy storage. Furthermore, similar results could be obtained by different methods such as stable-state analysis in the frequency …
Confirmation Of Anomalous-Heat Report, Steven B. Krivit, Melvin H. Miles
Confirmation Of Anomalous-Heat Report, Steven B. Krivit, Melvin H. Miles
Journal of Electrochemistry
This study identifies, for the first time, critical calculation errors made by Nathan Lewis and his co-authors, in their study presented on May 1, 1989, at the American Physical Society meeting in Baltimore, Maryland. Lewis et al. analysed calorimetrically measured heat results in nine experiments reported by Martin Fleischmann and his co-authors. According to the Lewis et al. analysis, each of the experiments, where calculated for no recombination, showed anomalous power losses. When we used the same raw data, our corrected calculations indicate that each experiment showed anomalous power gains. As such, these data suggest the possibility of a new, …
Automated Workflow For Redox Potentials And Acidity Constants Calculations From Machine Learning Molecular Dynamics, Feng Wang, Jun Cheng
Automated Workflow For Redox Potentials And Acidity Constants Calculations From Machine Learning Molecular Dynamics, Feng Wang, Jun Cheng
Journal of Electrochemistry
Redox potentials and acidity constants are key properties for evaluating the performance of energy materials. To achieve computational design of new generation of energy materials with higher performances, computing redox potentials and acidity constants with computational chemistry have attracted lots of attention. However, many works are done by using implicit solvation models, which is difficult to be applied to complex solvation environments due to hard parameterization. Recently, ab initio molecular dynamics (AIMD) has been applied to investigate real electrolytes with complex solvation. Furthermore, AIMD based free energy calculation methods have been established to calculate these physical chemical properties accurately. However, …
Brain-Inspired Continual Learning: Robust Feature Distillation And Re-Consolidation For Class Incremental Learning, Hikmat Khan, Nidhal Carla Bouaynaya, Ghulam Rasool
Brain-Inspired Continual Learning: Robust Feature Distillation And Re-Consolidation For Class Incremental Learning, Hikmat Khan, Nidhal Carla Bouaynaya, Ghulam Rasool
Henry M. Rowan College of Engineering Departmental Research
Artificial intelligence and neuroscience have a long and intertwined history. Advancements in neuroscience research have significantly influenced the development of artificial intelligence systems that have the potential to retain knowledge akin to humans. Building upon foundational insights from neuroscience and existing research in adversarial and continual learning fields, we introduce a novel framework that comprises two key concepts: feature distillation and re-consolidation. The framework distills continual learning (CL) robust features and rehearses them while learning the next task, aiming to replicate the mammalian brain's process of consolidating memories through rehearsing the distilled version of the waking experiences. Furthermore, the proposed …
Augmented Finite Control Set Mpc Design Technique For Wide Speed Range Control Of Permanent Magnet Synchronous Motor Drives, Francis Mwasilu
Augmented Finite Control Set Mpc Design Technique For Wide Speed Range Control Of Permanent Magnet Synchronous Motor Drives, Francis Mwasilu
Tanzania Journal of Engineering and Technology (TJET)
The effective motion control task is highly influencing the final drive performance in wide-range motor drives applications such as electric vehicles (EVs), washing machines, compressors, elevators and lathe machines. Recently, permanent magnet synchronous motor (PMSM) drive has been widely employed in these applications to achieve desired performances such as high efficiency, high torque requirements with minimum size “occupancy”. The PMSM drive features combining with these modern drive applications are highly nonlinear and the desired operation requirements demand high-performance control schemes with fast system response and robustness features. Linear control schemes are usually implemented to drive the PMSM that entail trade …
Steminism: Analyzing Factors That Improve Retention Of Women In Stem, Kira Carter, Jane Kelley, Jason Vasser-Elong, Rc Patterson
Steminism: Analyzing Factors That Improve Retention Of Women In Stem, Kira Carter, Jane Kelley, Jason Vasser-Elong, Rc Patterson
Dissertations
Our co-authored research ‘Steminism: Analyzing Factors That Improve Retention for Women as STEM Majors’ analyzed factors that contributed to the retention of women in science, technology, engineering, and mathematics (STEM) programs at Missouri University of Science & Technology (Missouri S&T). Women make up half of the US population, and while careers in (STEM) are an integral part of the US economy, women are underrepresented in these career fields. The purpose of our dissertation is to address the underrepresentation of women in STEM majors. Our methodology included homogeneous sampling to collect qualitative data. More specifically, we consulted with academic advisors and …
Pre‑Sizing Online Tool For Photovoltaic Water Pumping System: Development, Testing, Validation, And Evaluation, Sameh O. Abdellatif, Hani Ghali, Ibrahem Mohamed Mahmoud, Ahmed Hatem, Abdullah Hatem
Pre‑Sizing Online Tool For Photovoltaic Water Pumping System: Development, Testing, Validation, And Evaluation, Sameh O. Abdellatif, Hani Ghali, Ibrahem Mohamed Mahmoud, Ahmed Hatem, Abdullah Hatem
Electrical Engineering
No abstract provided.
Path And Strategy Of Pollution And Carbon Reduction By Digitization In Electric Power Enterprises, Xiaohong Chen, Runcheng Tang, Dongbin Hu, Xuesong Xu, Xiangbo Tang, Guodong Yi, Weiwei Zhang
Path And Strategy Of Pollution And Carbon Reduction By Digitization In Electric Power Enterprises, Xiaohong Chen, Runcheng Tang, Dongbin Hu, Xuesong Xu, Xiangbo Tang, Guodong Yi, Weiwei Zhang
Bulletin of Chinese Academy of Sciences (Chinese Version)
With the extensive application and innovation of digital technology in the energy sector, digital technology has become increasingly crucial for the power industry to achieve the goal of reducing pollution and carbon emissions. How digital technology enables electric power enterprises to achieve this goal has attracted much attention. Firstly, the study analyzes the progress of digital technology applications in pollution reduction and carbon reduction in electric power enterprises. Then, it identifies the existing problems in the current application of digital technology in the power industry for reducing pollution and carbon emissions. Finally, it explores the potential ways and approaches of …
Analysis And Recommendations For Energy Conservation And Carbon Emission Reduction In Industry Boosted By Digital Energy Management Systems, Duanyang Geng, Tong Xu, Qinghua Zhu, Steve Evans
Analysis And Recommendations For Energy Conservation And Carbon Emission Reduction In Industry Boosted By Digital Energy Management Systems, Duanyang Geng, Tong Xu, Qinghua Zhu, Steve Evans
Bulletin of Chinese Academy of Sciences (Chinese Version)
Energy consumption during production processes in the industry is a main source of carbon dioxide emissions. Therefore, for China’s dual-carbon goals, industrial enterprises need to focus on reducing energy waste to achieve energy-efficient production, thereby effectively reducing carbon emissions in industrial production. In recent years, with the continuous development and popularization of digital technology, digital energy management systems have played a crucial role in energy saving by visualizing invisible energy in the industry. In this context, this study first analyses the current status of digital energy management system applications in the UK, the US, Germany, and Sweden, summarizes their characteristics …
Impact Of Chips And Science Act Of 2022 On China's Related Industries And Policy Suggestions, Jiuling Shi, Yongmiao Hong, Ying Liu
Impact Of Chips And Science Act Of 2022 On China's Related Industries And Policy Suggestions, Jiuling Shi, Yongmiao Hong, Ying Liu
Bulletin of Chinese Academy of Sciences (Chinese Version)
As the cornerstone of modern information technology, chips are the strategic commanding heights of competition game and industrial development of countries all over the world. In recent years, the United States has taken advantage of its technological advances to successively introduce chip laws against China, which seriously violates the laws of market economy and has a significant impact on the global semiconductor industry chain. This study first sorts out the development pattern of the global semiconductor industry, and then introduces the background, content and purpose of CHIPS and Science Act of 2022. Then, it analyzes the impact of the …
Understanding Quadrature Modulation By Designing A 7mhz Iq Test Bench To Encode The Polybius Square, William Lee Bradley
Understanding Quadrature Modulation By Designing A 7mhz Iq Test Bench To Encode The Polybius Square, William Lee Bradley
Dissertations and Theses
This thesis outlines the design of an IQ Test Bench that allows for experimentation of quadrature modulation techniques. Quadrature modulation utilizes two signals I and Q, 90° out of phase from each other, to greatly increase communication data rates. Using Desmos, a thorough mathematical analysis of waveform mixing is presented, and constellation diagrams are plotted from the results. From this an ancient fire signaling technique known as the Polybius Square is encoded into the system. The IQ Test Bench is built from fundamental components that would be contained within an RFFE: a local oscillator and two frequency mixers. The LO …
Fractional Delay-Dependent Load Frequency Controller Design For A Single-Area Power System With Communication Delay, Erhan Yumuk
Fractional Delay-Dependent Load Frequency Controller Design For A Single-Area Power System With Communication Delay, Erhan Yumuk
Turkish Journal of Electrical Engineering and Computer Sciences
This paper proposes a fractional delay-dependent load frequency control design approach for a single-area power system with communication delay based on gain and phase margin specifications. In this approach, the closed-loop reference transfer function relies on the delayed Bode’s transfer function. The gain and phase margin specifications are established in order to optimize the reference model based on three time-domain performance indices. Here, a category of fractional-order model is employed to describe the single-area power system incorporating communication delay. The controller parameters are determined using the fractional-order system model and optimal closed-loop reference model. Then, a delay-dependent control mechanism is …
Motion Magnification-Inspired Feature Manipulation For Deepfake Detection, Aydamir Mirzayev, Hamdi Di̇bekli̇oğlu
Motion Magnification-Inspired Feature Manipulation For Deepfake Detection, Aydamir Mirzayev, Hamdi Di̇bekli̇oğlu
Turkish Journal of Electrical Engineering and Computer Sciences
Recent advances in deep learning, increased availability of large-scale datasets, and improvement of accelerated graphics processing units facilitated creation of an unprecedented amount of synthetically generated media content with impressive visual quality. Although such technology is used predominantly for entertainment, there is widespread practice of using deepfake technology for malevolent ends. This potential for malicious use necessitates the creation of detection methods capable of reliably distinguishing manipulated video content. In this work we aim to create a learning-based detection method for synthetically generated videos. To this end, we attempt to detect spatiotemporal inconsistencies by leveraging a learning-based magnification-inspired feature manipulation …
Error Performance Enhancement And Complexity Reduction In Ofdm Systems Via Coordinate Interleaving Under Practical Impairments, Mustafa Anıl Reşat, Armed Tusha, Seda Doğan Tusha, Serdar Özyurt, Hüseyin Arslan
Error Performance Enhancement And Complexity Reduction In Ofdm Systems Via Coordinate Interleaving Under Practical Impairments, Mustafa Anıl Reşat, Armed Tusha, Seda Doğan Tusha, Serdar Özyurt, Hüseyin Arslan
Turkish Journal of Electrical Engineering and Computer Sciences
In this work, subcarrier coordinate interleaving (CI) is implemented to orthogonal frequency division multiplexing (OFDM) systems with the aim of both enhancing the error performance and reducing the implementation complexity. To this end, the modulated symbols are independently chosen from a modified M-ary amplitude-shift keying signal constellation under a specific CI strategy. In addition to doubling the diversity level of the original OFDM scheme, the adopted CI approach also drastically reduces the inverse fast Fourier transform (IFFT) size at the transmit side by guaranteeing the first half of the input vector to be identical with the second half at the …
Artificial Intelligence-Based Evaluation Of The Factors Affecting The Sales Of An Iron And Steel Company, Mehmet Pekkaya, Zafer Uysal, Aytaç Altan, Seçkin Karasu
Artificial Intelligence-Based Evaluation Of The Factors Affecting The Sales Of An Iron And Steel Company, Mehmet Pekkaya, Zafer Uysal, Aytaç Altan, Seçkin Karasu
Turkish Journal of Electrical Engineering and Computer Sciences
It is important to predict the sales of an iron and steel company and to identify the variables that influence these sales for future planning. The aim in this study was to identify and model the key factors that influence the sales volume of an iron and steel company using artificial neural networks (ANNs). We attempted to obtain an integrated result from the performance/sales levels of 5 models, to use the ANN approach with hybrid algorithms, and also to present an exemplary application in the base metals industry, where there is a limited number of studies. This study contributes to …
Fast Grid Search: A Grid Search-Inspired Algorithm For Optimizing Hyperparameters Of Support Vector Regression, Mustafa Açikkar
Fast Grid Search: A Grid Search-Inspired Algorithm For Optimizing Hyperparameters Of Support Vector Regression, Mustafa Açikkar
Turkish Journal of Electrical Engineering and Computer Sciences
This study presents a fast hyperparameter optimization algorithm based on the benefits and shortcomings of the standard grid search (GS) algorithm for support vector regression (SVR). This presented GS-inspired algorithm, called fast grid search (FGS), was tested on benchmark datasets, and the impact of FGS on prediction accuracy was primarily compared with the GS algorithm on which it is based. To validate the efficacy of the proposed algorithm and conduct a comprehensive comparison, two additional hyperparameter optimization techniques, namely particle swarm optimization and Bayesian optimization, were also employed in the development of models on the given datasets. The evaluation of …
Milp Modeling Of Matrix Multiplication: Cryptanalysis Of Klein And Prince, Murat Burhan İlter, Ali Aydın Selçuk
Milp Modeling Of Matrix Multiplication: Cryptanalysis Of Klein And Prince, Murat Burhan İlter, Ali Aydın Selçuk
Turkish Journal of Electrical Engineering and Computer Sciences
Mixed-integer linear programming (MILP) techniques are widely used in cryptanalysis, aiding in the discovery of optimal linear and differential characteristics. This paper delves into the analysis of block ciphers KLEIN and PRINCE using MILP, specifically calculating the best linear and differential characteristics for reduced-round versions. Both ciphers employ matrix multiplication in their diffusion layers, which we model using multiple XOR operations. To this end, we propose two novel MILP models for multiple XOR operations, which use fewer variables and constraints, proving to be more efficient than standard methods for XOR modeling. For differential cryptanalysis, we identify characteristics with a probability …
Differentially Private Online Bayesian Estimation With Adaptive Truncation, Sinan Yildirim
Differentially Private Online Bayesian Estimation With Adaptive Truncation, Sinan Yildirim
Turkish Journal of Electrical Engineering and Computer Sciences
In this paper, a novel online and adaptive truncation method is proposed for differentially private Bayesian online estimation of a static parameter regarding a population. A local differential privacy setting is assumed where sensitive information from individuals is collected on an individual level and sequentially. The inferential aim is to estimate, on the fly, a static parameter regarding the population to which those individuals belong. We propose sequential Monte Carlo to perform online Bayesian estimation. When individuals provide sensitive information in response to a query, it is necessary to corrupt it with privacy-preserving noise to ensure the privacy of those …
A Novel Extended Reaction Force/Torque Observer With Impedance Control, İlkay Turaç Özçeli̇k, Abdurrahman Eray Baran
A Novel Extended Reaction Force/Torque Observer With Impedance Control, İlkay Turaç Özçeli̇k, Abdurrahman Eray Baran
Turkish Journal of Electrical Engineering and Computer Sciences
This paper proposes a new extended version of the reaction force observer (RFOB) for high-precision motion control systems. The RFOB has been proven to be useful for many applications in the literature. However, because of the low-pass filter present inside of the RFOB, it has certain limitations. In this study, a new algorithm is proposed to compensate for filtering-based errors in the classical RFOB structure. The algorithm includes the differentiation of the observed force and scaling with a proper value. However, since the force has a noisy nature, differentiation also affects the signal’s stability and performance. To resolve this issue, …
Traffic Signal Optimization Using Multiobjective Linear Programming For Oversaturated Traffic Conditions, Mustafa Murat Coşkun, Cevat Şener, İsmail Hakkı Toroslu
Traffic Signal Optimization Using Multiobjective Linear Programming For Oversaturated Traffic Conditions, Mustafa Murat Coşkun, Cevat Şener, İsmail Hakkı Toroslu
Turkish Journal of Electrical Engineering and Computer Sciences
In this study, we present a framework designed to optimize signals at intersections experiencing oversaturated traffic conditions, utilizing mixed-integer linear programming (MILP) techniques. The proposed MILP solutions were developed with different objective functions, namely a reduction in the total remaining queue and fair distribution of the remaining queue after each signal cycle. Our framework contains two distinct stages. The initial stage applies two distinct MILP methodologies, while the subsequent stage employs a neighborhood search method to further reduce the delays associated with the green signal timings derived from the first stage. Ultimately, to evaluate their effectiveness across various intersections, we …
Grey Wolf Optimization Algorithm-Based Robust Neural Learning Control Of Passive Torque Simulators With Predetermined Performance, Seyyed Amirhossein Saadat, Mohammad Mehdi Fateh, Javad Keighobadi
Grey Wolf Optimization Algorithm-Based Robust Neural Learning Control Of Passive Torque Simulators With Predetermined Performance, Seyyed Amirhossein Saadat, Mohammad Mehdi Fateh, Javad Keighobadi
Turkish Journal of Electrical Engineering and Computer Sciences
In flight control systems, the actuators need to tolerate aerodynamic torques and continue their operations without interruption. To this end, using the simulators to test the actuators in conditions close to the real flight is efficient. On the other hand, achieving the guaranteed performance encounters some challenges and practical limitations such as unknown dynamics, external disturbances, and state constraints in reality. Thus, this article attempts to present a robust adaptive neural network learning controller equipped with a disturbance observer for passive torque simulators (PTS) with load torque constraints. The radial basis function networks (RBFNs) are employed to identify the unknown …