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2024 International Conference on Quantum Computing and Engineering

作者： Bergerault, Alexandre Fortunato, Daniel Abreu, Rui Univ Porto Fac Phys & Astron QUARMEN Porto Portugal Univ Porto Fac Engn INESC ID Porto Portugal

ISBN: (纸本)9798331541378

Fixed margin binary matrices are used across various scientific fields. However, generating such matrices remains a complicated computational task using classical algorithms since the best algorithm performs in exponential time. In this paper, we model this problem using a Quadratic Unconstrained Binary optimization (QUBO). Furthermore, we use D-Wave's Quantum Annealing computer and their simulator to generate these matrices. Results obtained through the simulator attest to the capacity of our solution to effectively generate fixed margin binary matrices up to size 9 x 9 (constraint based on qubits availability). Results obtained from the quantum computer significantly suffer from noise compared to the simulator-based ones;however, we still get exact results with less effectiveness. Our solution and results are publicly available at https://github. com/Niten- lux/d- wave- qubo- solver.

关键词： QUBO Quantum Annealing Fixed Margin Binary Matrices optimization algorithm Quantum Computing

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An optimal membership function based Fuzzy-PI^λ stabilizer design to suppress low frequency oscillation in synchronous generator

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RESULTS IN CONTROL AND optimization 2024年 14卷

作者： Acharya, Debasis Das, Dushmanta Kumar Natl Inst Technol Nagaland Dept Elect & Elect Engn Dimapur 797103 India

An optimal membership function-based fractional order fuzzy proportional integral (Fuzzy-PI lambda) power system stabilizer (PSS) is designed to suppress low frequency oscillation (LFO) in a synchronous generator connected to an infinite bus power system. Speed deviation and the change in speed deviation of synchronous generator due to LFO are taken as inputs of the fuzzy controller, and the parameters of a fractional-order PI controller (proportional gain, integral gain, and the fractional term in integral control action) are taken as fuzzy output variables. The range, scaling, and shape of the membership functions of the fuzzy controller are optimized such that it can tune the fractional order proportional integral (PI lambda) stabilizer under any disturbance or parametric uncertainty in the synchronous generator. The advantage of the proposed stabilizer is that it can handle a wide range of disturbances and adjust the gains of the control parameters for the system. A nonlinear dynamic acceleration coefficient-based class-topper optimization is applied to optimize the fuzzy settings. The robustness and sensitivity of the proposed optimal Fuzzy-PI lambda stabilizer are verified under different scenarios for the synchronous generator and compared with available results.

关键词： Fractional order controller Synchronous generator Fuzzy controller optimization algorithm Power system stabilizer

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Optimizing Urban Electric Vehicle Charging Infrastructure Selection: An Approach Integrating GPS Data, Battery Levels, and Energy Availability 12

Optimizing Urban Electric Vehicle Charging Infrastructure Se...

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12th IFAC Symposium on Control of Power and Energy Systems (CPES)

作者： Belaid, Meriem El Beid, Said Hatim, Anas Cadi Ayyad Univ CISIEV Team Marrakech 40160 Morocco Cadi Ayyad Univ TIM Team Marrakech 40160 Morocco

This research paper offers a comprehensive exploratioli of how to enhance the charging infrastructure for Electric Vehicles (EVs) in urban settings. The analysis assesses three hypothetical charging infrastructures in a city, each with generators connected to thc national grid and strategically placed AC and DC chargers. The proposed method employs GPS data, EV battery levels, and energy availability across thc charging infrastructures. Using an optimization algorithm implemented via thc Pandapower Python library, the most appropriate charging infrastructure is identified for individual drivers. The algorithm considers factors such as GPS data and energy availability to suggest thc optimal charging station for each EV's battery level. This pioneering solution aims to streamline the charging process, enhance user experience, and encourage efficient use of urban charging infrastructure for electric vehicles.

关键词： Electric Vehicle (EV) Charging Infrastructure Urban Environments AC Chargers DC Chargers GPS Data Battery Levels optimization algorithm Pandapower Python Library Sustainable Transportation User Experience

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Energy, exergy and economic benefits deriving from LNG-fired power plant: Cold energy power generation combined with carbon dioxide capture

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RENEWABLE ENERGY 2022年 195卷 214-229页

作者： Ouyang, Tiancheng Tan, Jiaqi Wu, Wencong Xie, Shutao Li, Difan Guangxi Univ Sch Mech Engn Nanning 530004 Peoples R China Guangxi Univ Guangxi Key Lab Petrochem Resource Proc & Proc Int Nanning 530004 Peoples R China

According to The Paris Agreement, countries need to strictly control carbon emissions before global warming causes great damage to the environment. Therefore, how to reduce carbon emissions to restore carbon neutrality has become an inevitable life-and-death matter for all countries from a long-term perspective. In view of the ever-increasing LNG-fired power plants and the wasted LNG cold energy in vaporization process, a new environment-friendly cold energy utilization method is proposed to meet energy conservation and pollution reduction targets in this paper, integrating the organic Rankine cycle and the carbon dioxide capture cycle. Moreover, a full and deliberate comparison of pure and binary fluids is made to determine the optimal fluids of organic Rankine cycle (R600a) and carbon dioxide capture cycle (NH3 thorn R125), respectively. After being optimized by genetic algorithm, the thermal efficiency is 33.7% and exergy efficiency reaches 47.2%. Meanwhile, the net specific work and total carbon dioxide capture generated by the system are 110.1 kWh/tLNG and 0.78 t/tLNG. In terms of economic benefit, this cold energy utilization system can recover the total investment cost in 1.85 years. Thus, the practical application of this proposed method is completely feasible and economical, and it can recover capital in a short time.

关键词： LNG cold Energy utilization Carbon dioxide capture Thermal economy optimization algorithm

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A Novel PSO Based Fuzzy Controller for Robust Operation of Solid-State Transfer Switch and Fast Load Transfer in Power Systems

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IEEE ACCESS 2022年 10卷 37369-37381页

作者： Sebastian, Glorria Hannan, M. A. Al-Shetwi, Ali Q. Ker, Pin Jern Rahman, M. S. A. Mansur, M. Muttaqi, K. M. Univ Tenaga Nas Dept Elect & Elect Engn Kajang 43000 Malaysia Fahad Bin Sultan Univ Elect Engn Dept Tabuk 71454 Saudi Arabia Univ Tenaga Nas Inst Sustainable Energy Kajang 43000 Malaysia Univ Wollongong Sch Elect Comp & Telecommun Engn Wollongong NSW 2522 Australia

This paper proposes a novel particle swarm optimization (PSO) algorithm based fuzzy logic controller (FLC) for improving the performance of automatic solid-state transfer switch (SSTS) with respect to transfer time. The proposed technique generates adaptive membership functions (MFs) of voltage error and rate of change of voltage error for input and output based on the fitness function formulated by the PSO. An optimal PSO-based FLC (PSOF) fitness function is further employed to tune and minimize the mean absolute error (MAE) to improve the performance of the load transfer in a short duration. Results obtained from the proposed PSOF are compared with those obtained with the conventional FLC to validate the developed controller. It is observed that the proposed PSOF optimized controller can transfer the load faster than the conventional FLC controller. The accuracy of the developed PSOF is illustrated and investigated via simulation tests for SSTS in the IEEE 9-bus system. It can be concluded that the PSOF controller is better than the only fuzzy controller in all tested cases in terms of transfer time.

关键词： optimization Switches Fault detection Control systems Fuzzy logic Electrical fault detection Pulse width modulation Automatic solid-state transfer switch fuzzy control optimization algorithm power transfer load transfer power system faults

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A new trisection method for solving Lipschitz bi-objective optimization problems

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MATHEMATICS AND COMPUTERS IN SIMULATION 2021年 190卷 1186-1205页

作者： Naffeti, Bechir Ammar, Hamadi Carthage Univ Natl Sch Adv Sci & Technol Borj Cedria LR16ES08 Tunis Tunisia Carthage Univ Fac Sci Bizerte Bizerte Tunisia Carthage Univ Fac Econ & Management Nabeul Nabeul Tunisia

In this paper, we develop a branch and bounds algorithm to solve bound-construction bi-objective optimization problem. The proposed algorithm allows to determine an approximation of the Pareto optimal solutions sets in both spaces: decisions and objectives ones. By running alpha-dense space filling curves, we convert a multidimensional bi-objective optimization problem into a one-dimensional one. Hence it gets possible the implementation of the proposed algorithm when objectives depend on more than one decision variable. The proposed algorithm was applied on an engineering problem to find the working space of a robotic manipulator and the obtained results are promising. (C) 2021 International Association for Mathematics and Computers in Simulation (IMACS). Published by Elsevier B.V. All rights reserved.

关键词： optimization algorithm Bi-objective optimization Branch and bounds Trisection methods Lipschitz functions Pareto front Alienor technical

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I-GWO and Ex-GWO: improved algorithms of the Grey Wolf Optimizer to solve global optimization problems

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ENGINEERING WITH COMPUTERS 2021年第1期37卷 509-532页

作者： Seyyedabbasi, Amir Kiani, Farzad Istanbul Sabahattin Zaim Univ Engn & Nat Sci Fac Comp Engn Dept Istanbul Turkey Istanbul Arel Univ Engn & Architecture Fac Comp Engn Dept Istanbul Turkey

In this paper, two novel meta-heuristic algorithms are introduced to solve global optimization problems inspired by the Grey Wolf Optimizer (GWO) algorithm. In the GWO algorithm, wolves are likely to be located in regions close to each other. Therefore, as they catch the hunt (approaching the solution), they may create an intensity in the same or certain regions. In this case, the mechanism to prevent the escape of the hunt may not work well. First, the proposed algorithm is the expanded model of the GWO algorithm that is called expanded Grey Wolf Optimizer. In this method, the same as GWO, alpha, beta, and delta play the role of the main three wolves. However, the next wolves select and update their positions according to the previous and the first three wolves in each iteration. Another proposed algorithm is based on the incremental model and is, therefore, called incremental Grey Wolf Optimizer. In this method, each wolf updates its own position based on all the wolves selected before it. There is the possibility of finding solutions (hunts) quicker than according to other algorithms in the same category. However, they may not always guarantee to find a good solution because of their act dependent on each other. Both algorithms focus on exploration and exploitation. In this paper, the proposed algorithms are simulated over 33 benchmark functions and the related results are compared with well-known optimization algorithms. The results of the proposed algorithms seem to be good solutions for various problems.

关键词： Grey wolf optimizer (GWO) optimization algorithm Meta-heuristic Swarm intelligence

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Prediction of Surface Subsidence in Mining Areas Based on Ascending-Descending Orbits Small Baseline Subset InSAR and Neural Network optimization Models

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SENSORS 2024年第15期24卷 4770页

作者： Chang, Kangtai Zhao, Zhifang Zhou, Dingyi Tian, Zhuyu Wang, Chang Yunnan Univ Inst Int Rivers & Ecosecur Kunming 650500 Peoples R China Yunnan Univ Sch Earth Sci Kunming 650500 Peoples R China Yunnan Int Joint Lab China Laos Bangladesh Myanmar Kunming 650500 Peoples R China Res Ctr Domest High Resolut Satellite Remote Sensi Kunming 650500 Peoples R China Yunnan Key Lab Sanjiang Met & Resources Explorat & Kunming 650051 Peoples R China Changan Univ Coll Geol Engn & Geomat Xian 710054 Peoples R China Changan Univ Sch Informat Engn Xian 710064 Peoples R China

Surface subsidence hazards in mining areas are common geological disasters involving issues such as vegetation degradation and ground collapse during the mining process, which also raise safety concerns. To address the accuracy issues of traditional prediction models and study methods for predicting subsidence in open-pit mining areas, this study first employed 91 scenes of Sentinel-1A ascending and descending orbits images to monitor long-term deformations of a phosphate mine in Anning City, Yunnan Province, southwestern China. It obtained annual average subsidence rates and cumulative surface deformation values for the study area. Subsequently, a two-dimensional deformation decomposition was conducted using a time-series registration interpolation method to determine the distribution of vertical and east-west deformations. Finally, three prediction models were employed: Back Propagation Neural Network (BPNN), BPNN optimized by Genetic algorithm (GA-BP), and BPNN optimized by Artificial Bee Colony algorithm (ABC-BP). These models were used to forecast six selected time series points. The results indicate that the BPNN model had Mean Absolute Errors (MAE) and Root Mean Squared Errors (RMSE) within 7.6 mm, while the GA-BP model errors were within 3.5 mm, and the ABC-BP model errors were within 3.7 mm. Both optimized models demonstrated significantly improved accuracy and good predictive capabilities.

关键词： Sentinel-1A SBAS-InSAR two-dimensional deformation decomposition subsidence prediction optimization algorithm

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Flight Trajectory optimization of Sailplane After Rope Break

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JOURNAL OF AIRCRAFT 2021年第6期58卷 1229-1241页

作者： Collazo Garcia, Armando R. Ranjan, Prateek Chen, Kevin J. James, Kai A. Ansell, Phillip J. Univ Illinois Dept Aerosp Engn Urbana IL 61801 USA

A study was performed to characterize an optimum return trajectory for a sailplane after a rope-break failure during an aerotow launch procedure. The performance of an SGS 1-26E sailplane was simulated using the equations of motion for quasi-steady flight in a time-stepping routine and published aerodynamic polar data. A gradient-based optimization algorithm was implemented using the simulated trajectory considering the glide velocity, bank angles, and runway offset angle to determine the minimum rope-break altitude from which a successful return could be theoretically produced. The SGS 1-26E sailplane was used in a flight-test campaign for empirical turn modeling and validation of the performance simulation. The minimum altitude where a return trajectory and downwind runway landing could be successfully completed after a rope-break event was observed to be 76.4 ft above ground level. A headwind and crosswind presence was observed to decrease the minimum rope-break altitude with increasing wind velocity up to a critical value, after which rope-break altitudes began to increase. These minimum rope-break altitudes serve as a theoretical indication that safe trajectories can be performed at lower failure altitudes than the commonly practiced decision altitude of 200 ft for certain wind conditions.

关键词： Agricultural Aircraft Trajectory optimization Runway Alignment Zero Lift Drag Coefficient Flight Testing optimization algorithm Steady Flight Flight Path Angle Critical Phases of Flight Pilots Operating Handbook

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Optimal Finite Time Cooperative Rendezvous for Multiple Vehicles

Optimal Finite Time Cooperative Rendezvous for Multiple Vehi...

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AIAA SciTech Forum

作者： Voleti, Rajeev S. Subbarao, Kamesh Univ Texas Arlington Dept Mech & Aerosp Engn Arlington TX 76019 USA

ISBN: (数字)9781624107115

ISBN: (纸本)9781624107115

This paper presents a novel solution for the cooperative, optimal multi-vehicle rendezvous problem, addressing both stationary and moving targets. The method employs a gain free, time-dependent optimal control problem for efficient vehicle convergence and adjusts optimal trajectories using a consensus protocol based on shared time-to-go information. Our two-stage approach involves (1) solving the optimal control problem for initial rendezvous trajectories, and (2) refining trajectories in real-time with a consensus-based adaptation protocol. The decentralized and scalable consensus algorithm leads to improved rendezvous performance. We also propose a centralized leader follower framework for objective based rendezvous in finite time. Numerical simulations demonstrate the method's effectiveness, superiority in convergence and adaptability, and the impact of communication topology on performance, providing valuable insights for practical implementation.

关键词： Pontryagin's Maximum Principle Numerical Simulation Consensus algorithm Model Predictive Control Quadrotor Boundary Value Problems Artificial Potential Fields Multi Agent Coordination optimization algorithm

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