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2020 IEEE Andescon Conference

作者： Montoya, Oscar Gil-Gonzalez, Walter Garces, A. Casilimas-Pena, A. Garrido, V. M. Univ Dist Francisco Jose de Caldas Engn Fac Bogota Colombia Inst Univ Pascual Bravo Fac Ingn Medellin Colombia Univ Tecnol Pereira Dept Elect Power Engn Pereira Colombia Univ Tecnol Bolivar Smart Energy Lab Cartagena Colombia

ISBN: (纸本)9781728193656

This paper addresses the problems of power flow and optimal power flow a nalysis considering voltage-dependent load models from the convex point of view. First, Taylor series expansion method is employed for linearizing the power flow equations generating a set of affine hyperplanes. Second, the sequential quadratic programming (SQP) approach is employed for adjusting the linearization point to eliminate the voltage estimation error between the exact and proposed convex models recursively. Two voltage-dependent load models are considered in our power flow and optimal power flow proposals which based on the exponential and polynomial models. General algebraic modeling system (GAMS) and its nonlinear optimization packages are employed for comparison purposes. Two DC-test systems with 6 and 21 nodes are used to validate the performance of the SQP proposed. The proposed SQP approach is implemented in MATLAB software with quadprog toolbox.

关键词： Direct-current networks optimal power flow analysis sequential quadratic programming Taylor's based series expansion method

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An inverse method for the reconstruction of thermal boundary conditions of semitransparent medium

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INTERNATIONAL JOURNAL OF HEAT AND MASS TRANSFER 2019年 134卷 574-585页

作者： Sun, Shuangcheng Wang, Guangjun Chen, Hong Zhang, Daqian Chongqing Univ Sch Energy & Power Engn 174 Shazheng St Chongqing 400044 Peoples R China Chongqing Univ Key Lab Low Grade Energy Utilizat Technol & Syst Minist Educ Chongqing 400044 Peoples R China

The sequential quadratic programming (SQP) algorithm is applied to reconstruct the time- and space-dependent boundary conditions in 1D and 2D radiative-conductive systems in this study. The coupled radiation-conduction heat transfer in absorbing, scattering and emitting media is solved by the discrete ordinate method combined with finite volume method, and the simulated boundary temperature is served as input for the inverse analysis. The SQP algorithm is employed as the optimization technique, through which the time-dependent boundary heat flux in 1D heat transfer problems and the space dependent boundary heat flux and convective heat transfer coefficient in 2D heat transfer problems are recovered. No prior information on the functional forms of the unknown boundary conditions is needed for inverse analysis. All the retrieval results show that the SQP algorithm is robust to the reconstruction of thermal boundary conditions in coupled radiative-conductive systems. The present inverse technique is proved to be more efficient and accurate than the conjugate gradient method, Levenberg-Marquardt method and particle swarm optimization algorithm. (C) 2019 Elsevier Ltd. All rights reserved.

关键词： Inverse heat transfer sequential quadratic programming Heat flux Convective heat transfer coefficient Coupled radiation and conduction

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A particle swarm optimization-based ensemble metaheuristic for long-term transmission network expansion planning

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Applied Soft Computing 2025年 179卷

作者： Libin Hong Guodong Wang Ruibin Bai School of Information Science and Technology Hangzhou Normal University Hangzhou PR China School of Computer Science University of Nottingham Ningbo PR China

To significantly enhance the exploration and exploitation capabilities of particle swarm optimization, it is beneficial to hybridize complementary algorithms, integrate effective methods at specific stages, and trigger a ‘bail-in’ mechanism when encountering a local optimum. In this study, a Particle Swarm Optimization-Based Hybrid Framework (PSO-BHF) is proposed. The framework includes a probability calculation method that considers particle improvement after using Covariance Matrix Adaptation Evolution Strategy (CMA-ES) to promote the convergence rate. Additionally, an opposition-based learning method is integrated to extend search regions and maintain particle diversity if the search becomes stagnant, while a Success History Intelligent Optimizer (SHIO) is employed to prevent premature convergence. Finally, the sequential quadratic programming (SQP) method is used to enhance exploitation around the best particle in the later stages of the evolutionary process. The novel framework was evaluated on CEC2017 benchmark functions and compared with 15 state-of-the-art PSO-based variants and 11 non-PSO-based algorithms. Ablation tests illustrate the effectiveness of individual mechanisms and their combinations. The framework is also applied to a real-world long-term Transmission Network Expansion Planning (TNEP) problem, which was released by GECCO 2023 and IEEE CEC 2023 for their joint competition on evolutionary computation in the energy domain. Experimental results demonstrate the impressive performance of the proposed framework compared to PSO-based variants and its effectiveness in the TNEP problem. However, it still needs time to catch up with the top tier of metaheuristics, specifically Differential Evolution (DE)-based algorithms.

关键词： CMA-ES Long-Term Transmission Network Expansion Planning Problem Opposition-based learning Particle Swarm Optimization sequential quadratic programming Success history intelligent optimizer

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Momentum Model-Based Minimal Parameter Identification of a Space Robot

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JOURNAL OF GUIDANCE CONTROL AND DYNAMICS 2019年第3期42卷 508-523页

作者： Naveen, B. Shah, Suril V. Misra, Arun K. Indian Inst Technol Dept Mech Engn NH 65 Nagaur Rd Jodhpur 342037 Rajasthan India McGill Univ Dept Mech Engn 817 Sherbrooke St West Montreal PQ H3A 0C3 Canada

Accurate information of inertial parameters is critical to motion planning and control of space robots. Before the launch, only a rudimentary estimate of the inertial parameters is available from experiments and CAD models. After the launch, on-orbit operations substantially alter the value of inertial parameters. In this work, a new momentum model-based method is proposed for identifying the minimal parameters of a space robot while on orbit. Minimal parameters are combinations of the inertial parameters of the links and uniquely define the momentum and dynamic models. Consequently, they are sufficient for motion planning and control of both the satellite and robotic arms mounted on it. The key to the proposed framework is the unique formulation of the momentum model in the linear form of minimal parameters. Further, to estimate the minimal parameters, a novel joint trajectory planning and optimization technique based on direction combinations of joints' velocity are proposed. The efficacy of the identification framework is demonstrated on a 12-degree-of-freedom, spatial, dual-arm space robot. The methodology is developed for tree-type space robots, requires just the pose and twist data, and is scalable with increasing number of joints.

关键词： Multi Arm Space Robots Motion Planning Satellites Robots Reaction Wheels Computing Trajectory Optimization sequential quadratic programming Particle Swarm Optimization Rigid Body Kinematics

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Factorization of saddle-point matrices in dynamical systems optimization-reusing pivots

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LINEAR ALGEBRA AND ITS APPLICATIONS 2019年 566卷 61-85页

作者： Kuratko, Jan Charles Univ Prague Fac Math & Phys Prague Czech Republic Czech Acad Sci Inst Comp Sci Pod Vodarenskou Vezi 271-2 Prague Czech Republic

In this paper we consider the application of direct methods for solving a sequence of saddle-point systems. Our goal is to design a method that reuses information from one factorization and applies it to the next one. In more detail, when we compute the pivoted LDLT factorization we speed up computation by reusing already computed pivots and permutations. We develop our method in the frame of dynamical systems optimization. Experiments show that the method improves efficiency over Bunch-Parlett and Bunch-Kaufman while delivering the same results. (C) 2019 Elsevier Inc. All rights reserved.

关键词： Saddle-point matrix Symmetric indefinite factorization Dynamical systems sequential quadratic programming

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Variational Analysis and sequential quadratic programming Approach for Robotics

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Procedia Technology 2012年 4卷 636-640页

作者： Ankit R Patel Mahesh A Patel Dhaval R Vyas Assistant Professor Department of Electrical Engineering L C Institute of TechnologyBhandu Mahesana Gujarat India

sequential quadratic programming (SQP) methods are widely used for solving practical optimization problems, especially in contact mechanics. The general structure of SQP methods is briefly introduced and it is shown how these methods can be adapted to field of Robotics, especially bipedal robot. Numerical results are presented for compass bipedal robot. This paper describes relationship between variational analysis and sequential quadratic programming using discrete mechanics and optimal control for bipedal robot.

关键词： Optimal Control Optimization Lagrangian and Hamiltonian Mechanics Robotics sequential quadratic programming

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Configuration and Parameter Design of Electrified Propulsion Systems for Three-Dimensional Transportation: A Comprehensive Review

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Green Energy and Intelligent Transportation 2025年

作者： Yunge Zou Yalian Yang Yuxin Zhang The College of Mechanical and Vehicle Engineering Chongqing University Chongqing 400044 The State Key Laboratory of Mechanical Transmissions for Advanced Equipment Chongqing University Chongqing 400044 China

The design of electrified propulsion systems, including their configuration and parameter layers, is crucial to overall vehicle performance. However, with the electrification of three-dimensional transportation (TDT) (air, ground, and sea) and net-zero emission requirements, new challenges and opportunities arise. The design of propulsion systems for aircraft, marines, and trains is inherently more challenging than that of ground vehicles, due to the significantly larger and more complex propulsions. Therefore, this paper provides a comprehensive review and discussion of the configuration design and parameter optimization methods for electrified propulsion systems. Firstly, four development periods of propulsion design are summarized, and the potential topological design space is analyzed from five aspects: energy storage devices, coupling devices, output types, actuators, and power elements. Then, for the first time, six design stages—configuration representation, comparison and modification, generation, physical layer screening, control layer screening, and configuration-parameter co-optimization—are systematically reviewed and evaluated. Then, the strengths and limitations of each stage are analyzed in detail, and the challenges for the propulsion design for TDT in each stage are discussed. Finally, research challenges and trends are discussed, providing useful inspiration and guidance for advancing the configuration design and sizing optimization of electrified propulsion systems for TDT.

关键词： Electrified vehicles Propulsion design Three-dimensional transportation Dynamic modeling Parameter LP Linear programming AWD All-Wheel-Drive MPC Model Predictive Control BD Bond-graph NNL Neural Network Learning CAV Connected and Automated Vehicle NOx Nitrogen Oxide CV conventional fuel vehicles NVH Noise Vibration and Harshness CVT Continuously Variable Transmission OEM Original Equipment Manufacturer CP Convex programming PG Planetary Gear DC/AC Direct current/alternating current PGT Planetary gear trains DP Dynamic programming (P)HEV (Plug-in) Hybrid Electric Vehicle DRM Dual-rotor motor PMP Pontryagin’s Minimization Principle ECMS Equivalent Consumption Minimization Strategy PAST Powertrain System Analysis Toolkit EERCS efficiency evaluation real-time control strategy PEARS power-weighted efficiency analysis for rapid sizing EMR Energetic Macroscopic Representation POG Power-Oriented Graph EMS Energy Management Strategy PSO Particle Swarm Optimization EREV Extended-Range Electric Vehicle PS Power Split ESS Energy Storage System QP quadratic programming EV Electric Vehicle RB Rule-based EVT Electric Variable Transmission RL Reinforcement Learning FC Fuel Cell R/H/S/P Ring gear/Carrier/Sun gear/Pinion gear FC-FEV Fuel Cell Full-Electric Vehicle SC Super capacitor FG Fixed Gear SERCA slope-weighted energy-based rapid control analysis FL Fuzzy Logic SOC State of Charge GA Genetic Algorithm SP-HEV Series-Parallel Hybrid Electric Vehicle GIS Geographical Information System SQP sequential quadratic programming GPS Global Positioning System TDT Three-dimensional transportation GT Game Theory TTD Track-type dozers (H)ESS (Hybrid) Energy Storage System V2B Vehicle-to-Building HEPS Hybrid electric propulsion system V2G Vehicle-to-Grid ITS Intelligent Transportation System V2H Vehicle-to-Home ICE Internal Combustion Engine V2I Vehicle-to-Infrastructure

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Construction site accident analysis using text mining and natural language processing techniques

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AUTOMATION IN CONSTRUCTION 2019年 99卷 238-248页

作者： Zhang, Fan Fleyeh, Hasan Wang, Xinru Lu, Minghui Dalarna Univ Dept Comp Engn S-79188 Falun Sweden Univ Nottingham Ningbo Res Ctr Fluids & Thermal Engn Ningbo 315100 Zhejiang Peoples R China Shanghai Jiao Tong Univ Dept Comp Sci & Engn Shanghai 200030 Peoples R China

Workplace safety is a major concern in many countries. Among various industries, construction sector is identified as the most hazardous work place. Construction accidents not only cause human sufferings but also result in huge financial loss. To prevent reoccurrence of similar accidents in the future and make scientific risk control plans, analysis of accidents is essential. In construction industry, fatality and catastrophe investigation summary reports are available for the past accidents. In this study, text mining and natural language process (NLP) techniques are applied to analyze the construction accident reports. To be more specific, five baseline models, support vector machine (SVM), linear regression (LR), K-nearest neighbor (KNN), decision tree (DT), Naive Bayes (NB) and an ensemble model are proposed to classify the causes of the accidents. Besides, sequential quadratic programming (SQP) algorithm is utilized to optimize weight of each classifier involved in the ensemble model. Experiment results show that the optimized ensemble model outperforms rest models considered in this study in terms of average weighted F1 score. The result also shows that the proposed approach is more robust to cases of low support. Moreover, an unsupervised chunking approach is proposed to extract common objects which cause the accidents based on grammar rules identified in the reports. As harmful objects are one of the major factors leading to construction accidents, identifying such objects is extremely helpful to mitigate potential risks. Certain limitations of the proposed methods are discussed and suggestions and future improvements are provided.

关键词： Construction site accident analysis Machine learning Text mining Natural language processing sequential quadratic programming Optimization

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Experimental research on noninvasive reconstruction of optical parameter fields based on transient radiative transfer equation for diagnosis applications

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JOURNAL OF QUANTITATIVE SPECTROSCOPY & RADIATIVE TRANSFER 2019年 222卷 1-11页

作者： Qi, Hong Zhao, Fang-Zhou Ren, Ya-Tao Qiao, Yao-Bin Wei, Lin-Yang Islam, Md Arafat Ruan, Li-Ming Harbin Inst Technol Sch Energy Sci & Engn Harbin 150001 Heilongjiang Peoples R China

The noninvasive reconstruction of optical parameter fields in participating phantom is investigated experimentally based on the measured time-resolved radiative signals, which are detected by the time-correlated single-photon counting system. The discrete ordinate method is employed to solve the forward transient radiative transfer equation to simulate the time-resolved radiative transfer in the physical phantom exposed to ultra-short pulse laser irradiation. On top of that, the sequential quadratic programming algorithm based on the generalized Gaussian Markov random field is applied to solve the inverse problem. To improve the computational efficiency, an adjoint equation technique is adopted to determine the gradient of objective function. Good agreement was obtained between the predicted optical parameter fields and realistic ones. All the reconstruction results demonstrate that the proposed reconstruction methods are proved to be accurate and efficient experimentally. (C) 2018 Elsevier Ltd. All rights reserved.

关键词： Optical parameter fields reconstruction sequential quadratic programming Time-resolved radiative signals The time-correlated single-photon counting system

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Device-to-Device Communications Underlaying Cellular Networks: To Use Unlicensed Spectrum or Not?

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IEEE TRANSACTIONS ON COMMUNICATIONS 2019年第9期67卷 6598-6611页

作者： Wu, Fanyi Zhang, Hongliang Di, Boya Wu, Jianjun Song, Lingyang Peking Univ Dept Elect Engn Beijing 100871 Peoples R China

In this paper, we consider device-to-device (D2D) communications as an underlay to cellular networks over both licensed and unlicensed spectrums, where long-term evolution (LTE) users utilize the spectrum orthogonally while D2D users share the spectrum with LTE users. In the system, each LTE and D2D user can access the licensed or unlicensed band for communications. To maximize the total throughput of the system, we leverage stochastic geometry to derive the throughput for each kind of user by modeling the deployment of users as Poisson point processes (PPPs), and investigate the spectrum access problem for these users. Since the problem is NP-hard, we propose a sequential quadratic programming (SQP)-based algorithm to obtain the corresponding suboptimal solutions. Theoretically, we evaluate the system performance by analyzing the throughput regions. Simulation results validate the accuracy of the geometric analysis and verify the effectiveness of the proposed algorithm.

关键词： Device-to-device unlicensed communications spectrum access stochastic geometry sequential quadratic programming

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