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41st Computers and Information in engineering Conference, CIE 2021, Held as Part of the ASME 2021 International Design engineering Technical Conferences and Computers and Information in engineering Conference, IDETC-CIE 2021

作者： Kuroyanagi, Takumi Yamada, Shuho Hiramatsu, Shigeki Unesaki, Hiroshi Kondo, Shuichi Aoyama, Kazuhiro Department of Systems Innovation School of Engineering The University of Tokyo Tokyo Japan Integrated Control System Development Div. Mazda Motor Corporation Hiroshima Japan Electronic Platform Development Dept. Mazda Motor Corporation Hiroshima Japan The Research into Artifacts Center for Engineering School of Engineering The University of Tokyo Tokyo Japan

ISBN: (纸本)9780791885376

Herein, we have confirmed the importance of formulating product proposals and product-development processes equipped to cope effectively with uncertainty in the early design stage. The objective of this study was to derive the target performance and design priority order taking into account uncertainties in system design. Following the concept of set-based design, the approach adopted was to secure a set of solutions as design space that satisfy the target variables demands, dividing the design space into several clusters and evaluating each of the clusters, then gradually narrowing the cluster as the design progresses, and finally extracting the solution space that is desirable. Priority order of design was developed based on the strategy of increasing the degree of freedom of the subsequent process. The effectiveness of the proposed method was verified using the model of a plug-in hybrid vehicle. From the results, we confirmed the existence of a trade-off between design and target variables preference and development risk, that it is possible to determine the extent to which the solution space can be narrowed, that the shape of the solution space determines the design priorities, and we were able to derive a desirable design priority order according to the target performance. Copyright © 2021 by ASME

关键词： systems analysis

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Data-Driven Modelling and Model Predictive control Design of a Nonlinear Auger-Based Pyrolysis Reactor

SSRN

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SSRN 2024年

作者： Adiprabowo, Arya Bhaskara Muharto, Bambang Prabowo, Wargiantoro Saputro, Frendy Rian Anggoro, Trisno Masfuri, Imron Sugeng, Dhani Avianto Rosyadi, Erlan Lang, Zi-Qiang KST BJ Habibie Energy Building 620-625 Indonesia Department of Automatic Control and Systems Engineering University of Sheffield SheffieldS1 3JD United Kingdom Department of Electrical Engineering Mathematics and Computer Science University of Twente Enschede7522 NB Netherlands Vehicle System Engineering Malaysia-Japan International Institute of Technology Universiti Teknologi Malaysia Kuala Lumpur54100 Malaysia Department of Chemical and Environmental Engineering Malaysia Japan International Institute of Technology Universiti Teknologi Malaysia Kuala Lumpur54100 Malaysia

Pyrolysis is a prominent technique to harvest energy while addressing the global waste problem. Product yield relies heavily on precise reactor temperature control in a pyrolysis process;thus, a representative mathematical model is necessary to design and evaluate the control system. Hence, this research aims to create a data-driven model of a 1 kg/h Auger-based pyrolysis (APR) plant and design a robust controller accordingly. The system is excited by using a pseudo-random binary signal (PRBS) to trigger process response and is recorded for 2 hours. Various models with different orders, such as Auto Regressive Exogeneous (ARX), Auto Regressive Moving Average Exogeneous (ARMAX), Box-Jenkins (BJ), and Output Error (OE) were created from the obtained data. The models were examined using best-fit percentage, final prediction error (FPE) and mean square error (MSE) criteria and validated using cross-correlation and auto-correlation functions. Two widely used and purpose-fit controllers, Proportional-Integral-Derivate (PID) and Model Predictive control (MPC), with output constraints, were designed and tuned for this application. Several operational scenarios were investigated, such as setpoint tracking and disturbance rejection. The best-fit models were selected and validated for TIC-3, TIC-4 and TIC-5, with 96.22%, 97.4% and 84.83% fitness criteria, respectively. Both controllers successfully satisfied all the tests with less than 2% steady-state error. However, MPC surpassed PID controllers in all aspects, such as 5-7 times faster settling time, negligible overshoot, and reduced integral absolute error (IAE) and integral square error (ISE) up to 44.75% and 5.45%, respectively. Nevertheless, MPC with input and output constraints performance pales compared to other controllers despite some adjustments with massive ISE and settling time above 3000 seconds. As a result, a recommendation to change the input actuator will be beneficial to unleash the benefit of MPC fully. © 2

关键词： Model predictive control

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Constrained optimal control of monotone systems with applications to battery fast-charging

arXiv

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arXiv 2023年

作者： Drummond, Ross Courtier, Nicola E. Howey, David A. Couto, Luis D. Guiver, Chris The Department of Automatic Control and Systems Engineering University of Sheffield Mappin St SheffieldS1 3JD United Kingdom The Department of Engineering Science University of Oxford 17 Parks Road OxfordOX1 3PJ United Kingdom The Department of Control Engineering and System Analysis Université libre de Bruxelles BrusselsB-1050 Belgium The School of Engineering & the Built Environment Edinburgh Napier University EdinburghEH10 5DT United Kingdom

Enabling fast charging for lithium ion batteries is critical to accelerating the green energy transition. As such, there has been significant interest in tailored fast-charging protocols computed from the solutions of constrained optimal control problems. Here, we derive necessity conditions for a fast charging protocol based upon monotone control systems theory. Copyright © 2023, The Authors. All rights reserved.

关键词： Optimal control systems

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Data-driven feedback linearisation using model predictive control

arXiv

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arXiv 2022年

作者： Floren, Merijn Classens, Koen Oomen, Tom Noël, Jean-Philippe nic System Dynamics Division Celestijnenlaan 300 Leuven3001 Belgium Eindhoven University of Technology Department of Mechanical Engineering Control Systems Technology Group PO Box 513 MB Eindhoven5600 Netherlands

Linearising the dynamics of nonlinear mechanical systems is an important and open research area. In this paper, we adopt a data-driven and feedback control approach to tackle this problem. A model predictive control architecture is developed that builds upon data-driven dynamic models obtained using nonlinear system identification. The overall methodology shows a high degree of performance combined with significant robustness against imperfect modelling and extrapolation. These findings are demonstrated using large set of synthetic experiments conducted on a asymmetric Duffing oscillator and using an experimental prototype of a high-precision motion system. © 2022, CC BY.

关键词： Model predictive control

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A Survey of Fault Tolerance in Cloud Computing

A Survey of Fault Tolerance in Cloud Computing

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systems, Advanced Technologies and Knowledge (ISSATK), International Symposium of

作者： Om Kolthoum Elhajjej Nouha Alyaoui Samia Dardouri Karim Chabir Research Laboratory Modeling Aanalysis Control of System (MACS) LR16ES22 National engineering school of Gabes (ENIG) University of Gabes Tunisia Computer Science and Telecommunications Department Laboratory of Modeling Analysis and Control of Systems (MACS) Higher Institute of Applied Sciences and Technology Zarroug Gafsa Gafsa University Tunisia Department of Computer Science College of Computing and Information Technology Shaqra University Saudi Arabia InnoV’COM Laboratory-Sup’Com University of Carthage Tunisia

ISBN: (数字)9798331540173

ISBN: (纸本)9798331540180

This paper is designed to provide a comprehensive overview of the latest developments in fault tolerance methods for cloud computing. Maintaining high availability and reliability of cloud environments requires fault tolerance. This paper explores fault tolerance in the context of cloud computing and discusses recent challenges and innovations in the field. Moreover, it examines the ongoing research efforts to improve fault-tolerance architectures. At the end of the paper, the paper presents system-level metrics that are relevant to fault tolerance.

关键词： Measurement Surveys Cloud computing Fault tolerance Technological innovation Scalability Fault tolerant systems Computer architecture Software Software reliability

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Enhancing Traffic Flow Forecasting with Spatio-Temporal Information: A Case Study on Highway Networks in Belgium

Enhancing Traffic Flow Forecasting with Spatio-Temporal Info...

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International Conference on Instrumentation control and Automation (ICA)

作者： Muhammad Farhan Fathurrahman Arne Catteeuw Sidharta Gautama Angel Lopez Aguirre Endra Joelianto Herman Y. Sutarto Department Of Industrial Systems Engineering and Product Design Ghent University Ghent Belgium Department of Intelligent System PT. Pusat Riset Energi (PRE) Bandung Indonesia FlandersMake@UGent–Corelab ISyE Lommel Belgium Instrumentation and Control Research Group Faculty of Industrial Technology Institut Teknologi Bandung Bandung Indonesia

As the number of vehicles continues to increase every year, it is crucial to monitor traffic conditions effectively. Traffic forecasting serves as a valuable method in traffic management to support decision making. This study investigates the impact of utilizing spatio-temporal data for traffic flow forecasting, as opposed to forecasting each location individually. We compare spatio-temporal Long Short-Term Memory (LSTM), a machine-learning technique that utilizes spatially correlated sensor data in a network, and compare this to conventional LSTM and Seasonal ARIMA (SARIMA). Experiments have been conducted on counting loop data of a highway network in Belgium. We have investigated the performances of the forecasting model for different prediction horizons. The results show that spatial information improves the performance of the forecasting model and reduces the training time required. Further analysis show that the spatio-temporal LSTM improves majorities of detectors while the minorities detectors are degraded which imply the importances of network selection. The computational load of the spatio-temporal LSTM model is minimally impacted by the number of sensors in the network thus making it scalable. The results show that longer prediction horizons degrade the forecasting performance but the impact up to a 12 hour-horizon is not significant.

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Quantum Approximate Optimization Algorithm in Non-Markovian Quantum systems

arXiv

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arXiv 2022年

作者： Yue, Bo Xue, Shibei Pan, Yu Jiang, Min Department of Automation Shanghai Jiao Tong University The Key Laboratory of System Control and Information Processing Ministry of Education of China Shanghai200240 China State Key Laboratory of Industrial Control Technology Institute of Cyber-Systems and Control College of Control Science and Engineering Zhejiang University Hangzhou310027 China School of Electronics and Information Engineering Soochow University Suzhou215006 China

Although quantum approximate optimization algorithm (QAOA) has demonstrated its quantum supremacy, its performance on Noisy Intermediate-Scale Quantum (NISQ) devices would be influenced by complicated noises, e.g., quantum colored noises. To evaluate the performance of QAOA under these noises, this paper presents a framework for running QAOA on non-Markovian quantum systems which are represented by an augmented system model. In this model, a non-Markovian environment carrying quantum colored noises is modelled as an ancillary system driven by quantum white noises which is directly coupled to the corresponding principal system;i.e., the computational unit for the algorithm. With this model, we mathematically formulate QAOA as piecewise Hamiltonian control of the augmented system, where we also optimize the control depth to fit into the circuit depth of current quantum devices. For efficient simulation of QAOA in non-Markovian quantum systems, a boosted algorithm using quantum trajectory is further presented. Finally, we show that non-Markovianity can be utilized as a quantum resource to achieve a relatively good performance of QAOA, which is characterized by our proposed exploration rate. Copyright © 2022, The Authors. All rights reserved.

关键词： White noise

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Synthesis of the Decision Support system for controlling the Process of Combined Destruction of Butyl Rubber Vulcanizates 3

Synthesis of the Decision Support System for Controlling the...

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3rd International Conference on control systems, Mathematical Modeling, Automation and Energy Efficiency, SUMMA 2021

作者： Tikhomirov, German Karmanov, Andrey Zhatova, Victoria Popov, Alexey Obraztsov, Nikolay Podvalny, Evgeniy Voronezh State University Department of System Analysis and Management Voronezh Russia Voronezh State Technical University Department of Automated and Computing Systems Voronezh Russia Voronezh State University Department of Geoecology of Environmental Monitoring Voronezh Russia Voronezh State University of Engineering Technologies Department of Information and Control Systems Voronezh Russia Russian Presidental Academy of National Economy and Public Administration Department of Mathematics and Information Technologies in Management Moscow Russia

ISBN: (纸本)9781665439817

the article is devoted to solving the problems of synthesis of algorithmic support of the decision support system for the controlled destruction of resin vulcanizates of butyl rubber. As an object of research, the destruction processes have been selected, which are carried out by combining external destructive factors: ionization irradiation and subsequent thermomechanical treatment. Based on the results of the system analysis of the destruction process stages as control objects, the main and cross system connections between the input, internal parameters of the process and the physical properties of the final product have been revealed. The most preferred channels for controlling the rate of physical and chemical processes occurring during destruction have been selected. Using a combination of control actions, a method and an algorithm for controlling the stages of destruction has been proposed, which allows for programmed control of the operating parameters of the process to obtain reclaimed butyl rubber with target quality indicators. The structural synthesis of the mathematical support of the decision support system, which calculates the optimal values of the process parameters in accordance with the formed search criteria, has been carried out. An algorithm for controlling the destruction process has been developed, which calculates the optimal parameters of the process using the mathematical tools, which includes the Choquet integral, the Sugeno fuzzy measure, and a genetic algorithm for solving optimization problems. © 2021 IEEE.

关键词： Irradiation

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An IMU Error Correction Method Based on Multithreshold ZV Detection and SRCKF

An IMU Error Correction Method Based on Multithreshold ZV De...

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Cyber-Physical Social Intelligence (ICCSI), International Conference on

作者： Jialiang Luo Shichao Chen Yisheng Lv Wenqiao Sun Fan Yang Ruijie Xu The State Key Laboratory for Management and Control of Complex System State Key Laboratory of Multimodal Artificial Intelligence Systems Institute of Automation Chinese Academy of Sciences School of Information Engineering China University of Geosciences Beijing China The State Key Laboratory of Multimodal Artificial Intelligence Systems Institute of Automation Chinese Academy of Sciences The Center of National Railway Intelligent Transportation System Engineering and Technology China Academy of Railway Sciences Corporation Limited Beijing China The State Key Laboratory of Multimodal Artificial Intelligence Systems Institute of Automation Chinese Academy of Sciences Beijing China Transportation and Economics Research Institute and the Center of National Railway Intelligent Transportation System Engineering and Technology China Academy of Railway Sciences Corporation Limited China The State Key Laboratory for Management and Control of Complex System State Key Laboratory of Multimodal Artificial Intelligence Systems Institute of Automation Chinese Academy of Sciences College of Rail Transit Shan Dong JiaoTong University Jinan China Department of Aeronautical and Aviation Engineering The Hong Kong Polytechnic University Hong Kong China

With the rapid development and widespread application of Inertial Measurement Units (IMUs), IMU-based human localization has become critically important in environments lacking Global Navigation Satellite systems (GNSS) signals. Methods such as UWB/WIFI and other anchor-based localization have been employed to enhance the positioning accuracy. However, these methods are susceptible to the environmental interference and increased costs. In contrast, SINS-based localization methods eliminate reliance on the external data. However, this method can suffer from drift errors due to cumulative integration errors. Inertial navigation error correction techniques like Zero Detection Update Technology (ZUPT) provide potential solutions to address drift errors. This paper proposes an error correction method based on the multithreshold zero-velocity detection and Square Root Cubature Kalman Filter (SRCKF) updates. Compared to the single fixed threshold detection, the multi-threshold zero-velocity detection reduces the likelihood of missed zero velocity detection and false alarms, providing accurate time intervals for error correction. Experimental results demonstrate that the SRCKF-based algorithm reduces position deviation to approximately 0.3146 meters, corresponding to an error ratio of1.14%. The proposed method enables cost-effective and accurate pedestrian localization, driving advancements in the field.

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Data poisoning: issues, challenges, and needs

Data poisoning: issues, challenges, and needs

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7th IET Smart Cities Symposium (SCS 2023)

作者： Mohammad Aljanabi Alaa Hamza Omran Maad M Mijwil Mostafa Abotaleb El-Sayed M. El-kenawy Sahar Yousif Mohammed Abdelhameed Ibrahim Department of computer College of Education Aliarqai university Baghdad Iraq University of information technology and communications Baghdad Iraq Computer Techniques Engineering Department Baghdad College of Economic Sciences University Baghdad Iraq Department of System Programming South Ural State University Chelyabinsk Russia Department of Communications and Electronics Delta Higher Institute of Engineering and Technology Egypt Computer Science Department Computer Science & Information Technology College Anbar University Anbar Iraq Computer Engineering and Control Systems Department Faculty of Engineering Mansoura University Mansoura Egypt

Data poisoning attacks, where adversaries manipulate training data to degrade model performance, are an emerging threat as machine learning becomes widely deployed in sensitive applications. This paper provides a comprehensive overview of data poisoning including attack techniques, adversary incentives, impacts on security and reliability, detection methods, defenses, and key research gaps. We examine label flipping, instance injection, backdoors, and other attack categories that enable malicious outcomes ranging from IP theft to accidents in autonomous systems. Promising detection approaches include statistical tests, robust learning, and forensics. However, significant challenges remain in translating academic defenses like adversarial training and sanitization into practical tools ready for operational use. With safety and trustworthiness at stake, more research on benchmarking evaluations, adaptive attacks, fundamental tradeoffs, and real-world deployment of defenses is urgently needed. Understanding vulnerabilities and developing resilient machine learning pipelines will only grow in importance as data integrity is fundamental to developing safe artificial intelligence.

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