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IEEE International Symposium on Innovations in Intelligent systems and Applications (INISTA)

作者： Buket Sonbas Cobb Fethi Candan Department of Electrical-Electronics Engineering Harran University Sanliurfa Turkiye Department of Automatic Control and Systems Engineering University of Sheffield Sheffield United Kingdom

This research reveals the potential of Mediapipe with machine learning methods in addressing the critical need for real-time posture monitoring, offering a promising solution for creating secure work environments and improving health and safety conditions not only in the cargo industry but also in other fields, such as healthcare, sports, and industry. The findings indicate that the Random Forest Classifier demonstrates the highest accuracy in classifying untrained movements, indicating its potential for developing a posture correction warning system. Further research is needed to validate the findings and explore real-world applications. Overall, this study contributes to the advancement of workplace safety and sets the foundation for future developments in posture monitoring systems using Mediapipe and machine learning using Python programming.

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Novel Bandpass RLC-Filter 30

Novel Bandpass RLC-Filter

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30th Telecommunications Forum, TELFOR 2022

作者： Denisenko, Darya Prokopenko, Nikolay Butyrlagin, Nikolay Ivanov, Yuri Don State Technical University Department of scientific research Southern Federal University Department of Automatic Control Systems Rostov-on-Don Russia Don State Technical University Department of Information Systems and Radio Engineering Institute for Design Problems in Microelectronics of RAS Zelenograd Rostov-on-Don Russia Institute for Design Problems in Microelectronics of RAS Zelenograd Rostov-on-Don Russia Southern Federal University Department of Automatic Control Systems Rostov-on-Don Russia

ISBN: (数字)9781665472739

ISBN: (纸本)9781665472739

A new architecture of the band-pass RLC filter (RLC-PBF) is considered, in which independent adjustment of the pole frequency, pole quality factor and transmission coefficient is implemented with different resistors at constant values of the capacitance of the frequency-setting capacitor and the frequency-setting inductance. The results of the RLC-PBF simulation in the Micro-Cap environment are discussed, which confirm these properties. The basic mathematical expressions for the transfer function of the RLC-PBF and the parameters of its amplitude-frequency characteristic are obtained. The proposed RLC-PBF circuitry is recommended for adaptive signal filtering in radio engineering and measuring systems. Due to the appropriate choice of parameters of active and passive elements, the operation of the considered RLC-PBF is ensured both at low and at high frequencies. © 2022 IEEE.

关键词： Bandpass filters

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Excitation Optimization for Estimating Battery Health Parameters using Reinforcement Learning considering Information Content and Bias

Excitation Optimization for Estimating Battery Health Parame...

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American control Conference (ACC)

作者： Rui Huang Morgan Jones Xinfan Lin Department of Mechanical and Aerospace Engineering University of California Davis CA USA Department of Automatic Control and Systems Engineering The University of Sheffield Sheffield UK

Accurate parameter estimation has been a long-pursued objective in battery modeling and control practice. To this end, optimization of excitation to improve the estimation accuracy has been an emerging topic, since the quality of data critically determines the accuracy of estimation. However, there are several major drawbacks with existing approaches. First, the commonly used criterion for optimization, e.g., Fisher information, is limited in performance due to not considering the estimation bias caused by inevitable system uncertainties. In addition, alternative existing methods rely on a good a priori knowledge of the parameter to be estimated, which is intrinsically contradictory to the goal of estimation. To address these issues, we propose a reinforcement learning (RL) framework to learn the optimal policy for excitation generation that is robust to system uncertainties. In particular, the framework involves a non-additive objective/reward associated with the newly established optimization criterion, and a state augmentation technique is applied to address the ensuing challenge. It is shown that, when applied to estimate a key health-related battery electrochemical parameter, the RL-based approach achieves significantly higher objective value under nominal conditions, and reduces the estimation error by one-order-of-magnitude in the presence of uncertainties compared with the baseline in existing approaches.

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A Model of 6-10 kV Power Three-Core Cable for the Research of ITS Heating-Up in Normal and Emergency Operating Modes 4

A Model of 6-10 kV Power Three-Core Cable for the Research o...

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4th International Youth Scientific and Technical Conference Relay Protection and Automation, RPA 2021

作者： Kutumov, D.Yu. Mizonov, V.E. Yu, Shadrikova T. Shuin, V.A. Ivanovo State Power Engineering University Automatic Control of Electrical Power Systems Department Ivanovo Russia

ISBN: (纸本)9781728192703

One of the most significant consequences of short circuits and single phase to earth faults in 6-10 kV cable networks is cable insulation heating, which provides its further deflagration and damage of neighboring power supply systems' elements, which steps up consequential injury. Cable lines overheating during current overload leads to rapid insulation deterioration and cable lines damage rate increasing;similarly, cable heating during single phase to earth faults leads to its transformation to phase-to-phase short circuit, which requires faulted cable line emergency shutdown by relay protection devices operation and, moreover, can aid in cable deflagration when it is installed inside cable tunnels. Reference documents contain several calculation methods for cable line temperature definition both in steady-state and transient modes [1,2]. The main disadvantages of these methods are sufficiently restricted application sphere (only for symmetrical modes) and impossibility for accurate records of thermal conductivity and other thermophysical and geometric parameters of the researched cable line and external environment (soil, air, etc). For the solution of this problem an approach, which was described by F.H. Van Wormer in the 1950s [3] and also mentioned in [4-6], exists. According to this approach, the heated cable line and external environment are presented in the form of equivalent RC-branches, which simulates the process of transition and accumulation of heat. Nevertheless, during composition of such models an issue of computational space size and appropriate sampling rate of elementary RC-branches definition occurs. The model of cable line and external environment on the basis of so-called 'Markov's chains' [for example, 5] is also the case of interest, because it will allow to research qualitative characteristics of the system 'cable line-the external environment' in the context of its electromagnetic heating. The main goal of this research is to compile a digi

关键词： Thermal conductivity

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Minimizing risk in the scheduling of crudes in an oil refinery

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IFAC-PapersOnLine 2022年第7期55卷 809-814页

作者： Tomás García García-Verdier Gloria Gutiérrez Carlos Méndez Carlos G. Palacín César de Prada Systems Engineering and Automatic Control Department University of Valladolid Spain Center for Advanced Process Systems Engineering (CAPSE) INTEC (UNL - CONICET) Argentina

This paper focuses on formulating and solving the optimization of crude oil operations scheduling carried out in a system composed of a refinery and a marine terminal. The main challenge lies in coordinating the decisions made at both facilities and, at the same time, dealing with the uncertainties inherent in this activity. To tackle this problem, we present a continuous-time mixed-integer non-linear programming (MINLP) formulation. Furthermore, uncertainty in the ship arrival times is considered through a two-stage stochastic programming approach. Finally, the Conditional Value-at-Risk (CVaR) risk measure is employed to weigh the risk of having high costs relative to the worst scenarios. In this way, the proposed model is capable of supporting the decision-making process under uncertainty in an integral way.

关键词： Stochastic optimization Continuous-time representation Crude oil scheduling Uncertain oil supply Conditional Value-at-Risk

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Acoustic Echo Sensing for Robot Localization in Buried Pipe Networks

TechRxiv

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TechRxiv 2023年

作者： Worley, Rob Yu, Yicheng Horoshenkov, Kirill V. Anderson, Sean R. Department of Automatic Control and Systems Engineering University of Sheffield Sheffield United Kingdom Department of Mechanical Engineering University of Sheffield Sheffield United Kingdom

Robot localization in buried pipes presents a number of challenges, including the unavailability of methods such as a global positioning system, and the limited perspective of sensors such as vision. This paper addresses these challenges by using acoustic sensing, where signals sent by robots propagate long distances and around corners in the pipe environment, and can be used to estimate the distance to reflective features. It is shown that the reverberant environment causes a number of echoes which contain useful information. A novel algorithm for using this information in pose-graph optimization is proposed, and is shown to be necessary in comparison to a naive approach. The algorithm is demonstrated to be accurate and robust by measuring the error rate, which is the proportion of estimate error that was greater than a target threshold of 0.5 metres. The median error rate was 0 for measurement uncertainty 2.5 times larger than that found experimentally, and for motion uncertainty 4 times that which could be tolerated by an idealised loop-closure approach used for comparison. This work is the foundation for new data fusion methods for robot localization in buried pipes. © 2023, CC BY.

关键词： Mapping

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Online Conflict-Free Scheduling of Fleets of Autonomous Mobile Robots

Online Conflict-Free Scheduling of Fleets of Autonomous Mobi...

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IEEE International Conference on Automation Science and engineering (CASE)

作者： Francesco Popolizio Martina Vinetti Alvin Combrink Sabino Francesco Roselli Maria Pia Fanti Martin Fabian Department of Electrical Engineering Division of Systems and Control Chalmers University of Technology Göteborg Sweden Department of Electrical and Information Engineering Polytechnic of Bari Bari Italy

ISBN: (数字)9798350358513

ISBN: (纸本)9798350358520

This work presents a Fleet Manager for a fleet of Autonomous Mobile Robots (AMRs) that perform material handling tasks in a shared environment. The Fleet Manager assigns AMRs to newly released tasks, computes paths for them to travel to the task’s locations, and schedules their travel along the computed paths so that conflicts with other AMRs are avoided. The objective is for each AMR to complete its task as quickly as possible, to then be assigned a new *** Fleet Manager works online, assigning a released task to the AMR closest to the task’s location, and then computing the path and schedule to fit in with the already assigned and executing AMRs. Conflicts occur when, in order to reach their targets, AMRs would have to simultaneously occupy the same space. Resolving this is done by appropriate scheduling, or by moving idle AMRs out of the way. For fleet management to be practicable, the computation time for assigning an AMR to a task and computing its path and schedule must be negligible compared to other system *** were conducted to evaluate the performance of the Fleet Manager on a number of benchmark problem instances, counting up to hundreds of AMRs. The results show that the presented Fleet Manager can handle these systems quickly enough to be practically useful in real industrial scenarios.

关键词： Schedules Job shop scheduling Processor scheduling Benchmark testing Throughput Real-time systems Path planning Mobile robots Optimization Autonomous robots

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Complexity of linearized quadratic penalty for optimization with nonlinear equality constraints

arXiv

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arXiv 2024年

作者： Bourkhissi, Lahcen El Necoara, Ion Department of Automatic Control and Systems Engineering National University for Science and Technology Politehnica Bucharest Bucharest060042 Romania Department of Automatic Control and Systems Engineering National University for Science and Technology Politehnica Bucharest Bucharest060042 Romania Gheorghe Mihoc Caius Iacob Institute of Mathematical Statistics and Applied Mathematics the Romanian Academy Bucharest050711 Romania

In this paper we consider a nonconvex optimization problem with nonlinear equality constraints. We assume that both, the objective function and the functional constraints, are locally smooth. For solving this problem, we propose a linearized quadratic penalty method, i.e., we linearize the objective function and the functional constraints in the penalty formulation at the current iterate and add a quadratic regularization, thus yielding a subproblem that is easy to solve, and whose solution is the next iterate. Under a dynamic regularization parameter choice, we derive convergence guarantees for the iterates of our method to an ϵ first-order optimal solution in O(1/ϵ3) outer iterations. Finally, we show that when the problem data satisfy Kurdyka-Lojasiewicz property, e.g., are semialgebraic, the whole sequence generated by our algorithm converges and we derive convergence rates. We validate the theory and the performance of the proposed algorithm by numerically comparing it with the existing methods from the literature. © 2024, CC BY.

关键词： Linearization

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Simulation Analysis and Model Modification of the LWR Traffic Flow Theory

Simulation Analysis and Model Modification of the LWR Traffi...

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IEEE Workshop on Advanced Robotics and its Social Impacts, ARSO

作者： Yang Chen Jun Fu Anton Selivanov State Key Laboratory of Synthetical Automation for Process Industries Northeastern University Shenyang China Department of Automatic Control and Systems Engineering University of Sheffield UK

ISBN: (数字)9798350344639

ISBN: (纸本)9798350344646

The surge in urbanization and ensuing traffic congestion underscores the imperative for contemporary traffic flow control models. This paper explores the Lighthill-Whitham-Richards (LWR) theory in the macroscopic domain of traffic flow control. It evaluates the accuracy and mathematical logic of simulation performance of related models, namely Greenshields, Newell-Daganzo, Greenberg, Underwood, and California. This paper employs thorough simulations that utilize a holistic three-dimensional(3D) analysis based on time, location, and density. It provides a comprehensive comparison and discusses specific features of each model. Additionally, a modification to the macroscopic model is proposed. The modified model overcomes the shortcomings of performing well only in some specific short ranges and achieves a full range of application effects. The study offers valuable guidance for real-life scenario selections and applications in the traffic domain.

关键词： Analytical models Accuracy Urban areas Transportation Predictive models Mathematical models Numerical models

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A Review on Defense Mechanism against the Denial of Service and False Data Injection in Cyber-Physical Power systems

A Review on Defense Mechanism against the Denial of Service ...

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China International Electrical and Energy Conference (CIEEC)

作者： Zhuoran Zhou Jinning Zhang Xin Zhang Department of Automatic Control and Systems Engineering University of Sheffield Sheffield United Kingdom School of Engineering University of Leicester Leicester United Kingdom

Cyber-physical power system (CPPS), with its bi-directional power and information flows, is considered as the next generation of widely distributed and automated electrical power network. However, CPPS is vulnerable to malicious cyberattacks that can cause significant operational risk and financial loss to stakeholders, such as electricity system operators. The complexity of vulnerabilities, which arises from the heterogeneity and interdependency of physical and cyber domains, will present substantial challenges for the detection and prevention of cyberattacks. This paper provides a comprehensive review of the defense mechanisms in CPPS against coordinated and widespread cyberattacks. The most prevalent cyberattacks in the CPPS are denial-of-service (DoS) and false data injection (FDI) attacks. This paper examines the state-of-the-art prevention, detection, and mitigation technologies for these major mainstreams and coordinated cyberattacks. In particular, the advantages and disadvantages of popular cyberattack prevention sciences such as Game Theory, Optimization, control Theory, and Data-driven method are discussed. It reveals that cyberattack detection techniques have evolved from traditional state estimation to artificial intelligence-based methods. Finally, the challenges and opportunities for future research on cybersecurity in CPPS are identified.

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