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IEEE Transactions on Artificial Intelligence 2023年第4期4卷 722-733页

作者： Li, Dong Liu, Yiqi Huang, Daoping Xu, Chong South China University of Technology Key Laboratory of Autonomous Systems and Networked Control Ministry of Education School of Automation Science and Engineering Guangzhou510640 China Technical University of Denmark Process and Systems Engineering Center Department of Chemical and Biochemical Engineering Lyngby2800 Denmark South China University of Technology School of Automation Science and Engineering Guangzhou510640 China Gannan Normal University School of Physics and Electronic Information Ganzhou341000 China

To monitor industrial processes properly, soft-sensors are widely used to predict significant but difficult-to-measure quality variables. However, the prediction performances of traditional data-driven soft-sensors are usually unacceptable once suffering from high-nonlinear, high-dimension, and imblance data issues. Therefore, a semisupervised soft-sensor, which is learned by a just-in-time method with structure entropy clustering (SS-JITL-SEC), is proposed aiming to improve prediction performance with a simpler way. Inspired by a divide and conquer strategy, a novel SEC method is proposed to achieve several clusters and then to translate the highly complex and nonlinear modeling problems into simple and linear ones. Moreover, the training dataset is extended through a mixed SS labeling approach. Finally, dissimilarity-based JITL works together with the resulting clustering subdatasets to formulate a local adaptive prediction model. Two datasets from different types of wastewater treatment plants are used to verify the effectiveness of the proposed soft-sensor. The results show that the SS-JITL-SEC soft-sensor can achieve better prediction performance than other standard counterparts, and even for effective process monitoring with the resulted residuals. © 2020 IEEE.

关键词： Entropy

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Cost-optimal Fleet Management Strategies for Solar-electric Autonomous Mobility-on-Demand systems

Cost-optimal Fleet Management Strategies for Solar-electric ...

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International Conference on Intelligent Transportation

作者： Fabio Paparella Theo Hofman Mauro Salazar Department of Mechanical Engineering Control Systems Technology section Eindhoven University of Technology Eindhoven The Netherlands

This paper studies mobility systems that incorporate a substantial solar energy component, generated not only on the ground, but also through solar roofs installed on vehicles, directly covering a portion of their energy consumption. In particular, we focus on Solar-electric Autonomous Mobility-on-Demand systems, whereby solar-electric autonomous vehicles provide on-demand mobility, and optimize their operation in terms of serving passenger requests, charging and vehicle-to-grid (V2G) operations. We model this fleet management problem via directed acyclic graphs and parse it as a mixed-integer linear program that can be solved using off-the-shelf solvers. We showcase our framework in a case study of Gold Coast, Australia, analyzing the fleet's optimal operation while accounting for electricity price fluctuations resulting from a significant integration of solar power in the total energy mix. We demonstrate that using a solar-electric fleet can reduce the total cost of operation of the fleet by 10–15% compared to an electric-only counterpart. Finally, we show that for V2G operations using vehicles with a larger battery size can significantly lower the operational costs of the fleet, overcompensating its higher energy consumption by trading larger volumes of energy and even accruing profits.

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Optimal Design and Tuning of TID Power System Stabilizer for Multi-machine Power System Using Dandelion Optimizer

Optimal Design and Tuning of TID Power System Stabilizer for...

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International Conference on Artificial Intelligence in Renewable Energetic systems, IC-AIRES 2024

作者： Hattabi, Intissar Kheldoun, Aissa Bradai, Rafik Khettab, Soufian SET Laboratory Blida 1 University Faculty of Technology Electrical and Control Department Blida Algeria Laboratory of Signals and Systems Institute of Electrical and Electronic Engineering University M’hamed Bougara Boumerdes35000 Algeria LATSI Blida 1 University Faculty of Technology Electronics Department Blida09000 Algeria

ISBN: (纸本)9783031803000

In this study, we explore the enhancement of stability in a four-machine power system through the optimized tuning of Tilt-Integral-Derivative Power System Stabilizer (TID-PSS) parameters. We introduce a novel application of the Dandelion Optimizer (DO) algorithm, designed to provide robust damping and stability under fault conditions. To improve the effectiveness of the DO algorithm, we compare its performance with several established optimization techniques, including Particle Swarm Optimization (PSO), HGS (Hunger Games Search), HBA (Honey Badger Algorithm), EO (Equilibrium Optimizer), and AVOA (African Vulture Optimization algorithm. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2025.

关键词： Particle swarm optimization (PSO)

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Deep Forest-Based Fall Detection in Internet of Medical Things Environment

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Computer systems Science & engineering 2023年第6期45卷 2377-2389页

作者： Mohamed Esmail Karar Omar Reyad Hazem Ibrahim Shehata College of Computing and Information Technology Shaqra UniversityP.O.Box 33Shaqra11961Saudi Arabia Department of Industrial Electronics and Control Engineering Faculty of Electronic EngineeringMenoufia UniversityMenouf32952Egypt Computer Science Department Faculty of Computers and Artificial IntelligenceSohag UniversitySohag82524Egypt Department of Computer and Systems Engineering Faculty of EngineeringZagazig UniversityZagazig44519Egypt

This article introduces a new medical internet of things(IoT)framework for intelligent fall detection system of senior people based on our proposed deep forest *** cascade multi-layer structure of deep forest classifier allows to generate new features at each level with minimal hyperparameters compared to deep neural ***,the optimal number of the deep forest layers is automatically estimated based on the early stopping criteria of validation accuracy value at each generated *** suggested forest classifier was successfully tested and evaluated using a public SmartFall dataset,which is acquired from three-axis accelerometer in a *** includes 92781 training samples and 91025 testing samples with two labeled classes,namely non-fall and *** results of our deep forest classifier demonstrated a superior performance with the best accuracy score of 98.0%compared to three machine learning models,i.e.,K-nearest neighbors,decision trees and traditional random forest,and two deep learning models,which are dense neural networks and convolutional neural *** considering security and privacy aspects in the future work,our proposed medical IoT framework for fall detection of old people is valid for real-time healthcare application deployment.

关键词： Elderly population fall detection wireless sensor networks internet of medical things deep forest

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Analytic Mechanism for the Cumulative Effect of Wind Power Fluctuations from Single Wind Farm to Wind Farm Cluster

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CSEE Journal of Power and Energy systems 2022年第5期8卷 1290-1301页

作者： Gang Mu Fangze Wu Xiaoping Zhang Ziheng Fu Bai Xiao Key Laboratory of Modern Power System Simulation and Control&Renewable Energy Technology Ministry of Education(Northeast Electric Power University)Jilin 132012China Department of Electronic Electrical and Systems EngineeringSchool of EngineeringUniversity of BirminghamBirmingham B152TTU.K

The use of wind power is rapidly growing worldwide as a means of reducing carbon emissions for the energy *** has the world’s largest wind power installation and multiple large-scale wind farm clusters,each comprising dozens of wind *** the planning and operation of the power system,it is important to understand the power fluctuation characteristics of wind farm *** studies demonstrate that the relative power fluctuation of a wind farm cluster is less than that of a single wind *** this decreasing trend a random occurrence or does it have a regular pattern?This scientific question is addressed by investigating the mechanism of the cumulative effect of a wind farm *** this study,a cumulative model is proposed by examining the spatiotemporal relationships of wind power variations and wind farm *** gain function and critical cumulative frequency are defined as the foundations to analytically describing the cumulative *** investigating the cumulative effect mechanism,the relationship between power fluctuation and spatiotemporal parameters of the wind farm cluster are *** power fluctuation of a cluster can be predicted using the cumulative model even before it is completely *** mechanism of the cumulative effect is validated on the basis of the data of two actual wind farm clusters.

关键词： Analytic mechanism cumulative effect evolution regularity wind farm cluster wind power fluctuation

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Weighted Feedback-Based Quantum Algorithm for Excited States Calculation

Weighted Feedback-Based Quantum Algorithm for Excited States...

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Quantum Computing and engineering (QCE), IEEE International Conference on

作者： Salahuddin Abdul Rahman Özkan Karabacak Rafal Wisniewski Department of Electronic Systems Section of Automation and Control Aalborg University Aalborg Denmark Department of Mechatronics Engineering Kadir Has University Istanbul Turkey

ISBN: (数字)9798331541378

ISBN: (纸本)9798331541385

Drawing inspiration from the Lyapunov control technique for quantum systems, feedback-based quantum al-gorithms have been proposed for calculating the ground states of Hamiltonians. In this work, we consider extending these algorithms to tackle calculating excited states. Inspired by the weighted subspace-search variational quantum eigensolver al-gorithm, we propose a novel weighted feedback-based quantum algorithm for excited state calculation. We show that depending on how we design the weights and the feedback law, we can prepare the pth excited state or lowest energy states up to the pth excited state. Through an application in quantum chemistry, we show the effectiveness of the proposed algorithm, evaluating its efficacy via numerical simulations.

关键词： Quantum system Quantum algorithm Quantum chemistry Stationary state Numerical simulation Energy states

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Weighted Feedback-Based Quantum Algorithm for Excited States Calculation

arXiv

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arXiv 2024年

作者： Rahman, Salahuddin Abdul Karabacak, Özkan Wisniewski, Rafal Section of Automation and Control Department of Electronic Systems Aalborg University Aalborg Denmark Department of Mechatronics Engineering Kadir Has University Istanbul Turkey

Drawing inspiration from the Lyapunov control technique for quantum systems, feedback-based quantum algorithms have been proposed for calculating the ground states of Hamiltonians. In this work, we consider extending these algorithms to tackle calculating excited states. Inspired by the weighted subspace-search variational quantum eigensolver algorithm, we propose a novel weighted feedback-based quantum algorithm for excited state calculation. We show that depending on how we design the weights and the feedback law, we can prepare the pth excited state or lowest energy states up to the pth excited state. Through an application in quantum chemistry, we show the effectiveness of the proposed algorithm, evaluating its efficacy via numerical simulations. © 2024, CC BY.

关键词： Hamiltonians

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Feedback-Based Quantum Algorithm for Excited States Calculation

arXiv

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arXiv 2024年

作者： Rahman, Salahuddin Abdul Karabacak, Özkan Wisniewski, Rafal Automation and Control section Department of electronic systems Aalborg University Aalborg Denmark Department of Mechatronics Engineering Kadir Has University Istanbul Turkey

Recently, feedback-based quantum algorithms have been introduced to calculate the ground states of Hamiltonians, inspired by quantum Lyapunov control theory. This paper aims to generalize these algorithms to the problem of calculating an eigenstate of a given Hamiltonian, assuming that the lower energy eigenstates are known. To this aim, we propose a new design methodology that combines the layer-wise construction of the quantum circuit in feedback-based quantum algorithms with a new feedback law based on a new Lyapunov function to assign the quantum circuit parameters. We present two approaches for evaluating the circuit parameters: one based on the expectation and overlap estimation of the terms in the feedback law and another based on the gradient of the Lyapunov function. We demonstrate the algorithm through an illustrative example and through an application in quantum chemistry. To assess its performance, we conduct numerical simulations and execution on IBM’s superconducting quantum computer. © 2024, CC BY.

关键词： Lyapunov functions

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Feedback-Based Quantum Algorithm for Constrained Optimization Problems

arXiv

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arXiv 2024年

The feedback-based algorithm for quantum optimization (FALQON) has recently been proposed to find ground states of Hamiltonians and solve quadratic unconstrained binary optimization problems. This paper efficiently generalizes FALQON to tackle quadratic constrained binary optimization (QCBO) problems. For this purpose, we introduce a new operator that encodes the problem's solution as its ground state. Using control theory, we design a quantum control system such that the state converges to the ground state of this operator. When applied to the QCBO problem, we show that our proposed algorithm saves computational resources by reducing the depth of the quantum circuit and can perform better than FALQON. The effectiveness of our proposed algorithm is further illustrated through numerical simulations. © 2024, CC BY.

关键词： Constrained optimization

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Safety Assurance in Multi-UAV Formation Tracking control Amidst Missile Threats 7th

Safety Assurance in Multi-UAV Formation Tracking Control Am...

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7th Chinese Conference on Swarm Intelligence and Cooperative control, CCSICC 2023

作者： Li, Haoqi Hu, Jiangping Zhou, Qingrui Lv, Maolong Ghosh, Bijoy K. School of Automation Engineering University of Electronic Science and Technology of China Chengdu611731 China University of Electronic Science and Technology of China Huzhou313000 China Qian Xuesen Laboratory of Space Technology China Academy of Space Technology Beijing100094 China Air Traffic Control and Navigation College Air Force Engineering University Xian710051 China Department of Mathematics and Statistics Texas Tech University LubbockTX79409-1042 United States

ISBN: (纸本)9789819733279

The safety of multiple unmanned aerial vehicle (multi-UAV) systems threatened by enemy missiles is crucial for their effective formation control. In this paper, a distributed safety control strategy is developed that enables multi-UAV systems to execute formation tasks while avoiding enemy missiles. The proposed method considers enemy missiles as dynamic constraints on the multi-UAV system and is adaptable to changes in the number of UAVs. By ensuring each UAV remains within a defined safe set, the system can avoid incoming missiles while maximizing operational freedom for each UAV. The control strategy utilizes the backstepping control technique, making the computational process relatively inexpensive. Simulation results validate the effectiveness and adaptability of the proposed method in continuously changing threat environments. Our approach offers a promising solution for achieving safe and efficient multi-UAV cooperative operations in hostile environments. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024.

关键词： Lyapunov functions

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