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43rd Chinese Control Conference (CCC)

作者： Fan, Wensong Cai, Tao Lu, Kebing Yang, Panpan Qing, Haimei Beijing Inst Technol Natl Key Lab Autonomous Intelligent Unmanned Syst Beijing 100081 Peoples R China Beijing Inst Technol Sch Automat Beijing 100081 Peoples R China

ISBN: (纸本)9798350366907;9789887581581

This paper studies the time-optimal trajectory planning for manipulator. Conventional time-optimal trajectory planning utilizes the inverse solution, interpolation and intelligent optimization algorithms to search for the shortest time, making the process rather complex. To address this issue, we incorporate the kinematic equations and state transition equations into the existing two-stage algorithm used in unmanned aerial vehicles (UAVs), resulting in significantly improved computational speed and accuracy of the robotic arm's operation. The first stage predefines some resulting points related to path points and optimizes the robotic arm's kinematics and motion constraints as soft constraints to provide an initial solution for the second stage. In the second stage, based on the predetermined points of each trajectory segment provided by the first stage, the optimization problem is solved without the need for kinematic inverse solutions, in which the time intervals of each trajectory segment serve as optimization variables and the robotic arm's kinematics and motion constraints are used as hard constraints for optimization. Subsequently, the obtained joint points are interpolated using fifth-degree polynomials to form continuous joint trajectories. Comparative experiments with an improved particle swarm optimization algorithm verify that the proposed method exhibits higher optimization efficiency and achieves shorter optimized times.

关键词： Manipulator Time-Optimal Trajectory Planning two-stage algorithm Kinematics

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A two-stage Rapid Trajectory Optimization algorithm for Hypersonic Entry

A Two-Stage Rapid Trajectory Optimization Algorithm for Hype...

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IEEE Chinese Guidance, Navigation and Control Conference (CGNCC)

作者： Jinbo Wang Naigang Cui Changzhu Wei Aerospace Engineering Department Harbin Institute of Technology Harbin China

ISBN: (数字)9781538611715

ISBN: (纸本)9781538611722

A novel two-stage rapid trajectory optimization algorithm is presented to solve the hypersonic entry trajectory optimization problem. To circumvent the issue of initial guess of nonlinear programming (NLP) based methods, and to increase the computation speed of the algorithm to accommodate online applications, a convex optimization based algorithm is designed as an initial trajectory generator, which is the first stage of the two-stage algorithm. The second stage is the NLP-based pseudospectral method. Numerical experiments show that the overall computation time of the two-stage algorithm is much less than that of single pseudospectral method.

关键词： Hypersonic entry two-stage algorithm Rapid trajectory optimization Convex optimization Pseudospectral method trajectory optimization algorithms Convex function double-stage hypersonic speed computational time entry

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A two-stage Time-Optimal Trajectory Planning algorithm with No Inverse Kinematics for Manipulator

A Two-Stage Time-Optimal Trajectory Planning Algorithm with ...

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第43届中国控制会议

作者： Wensong Fan Tao Cai Kebing Lu Panpan Yang Haimei Qing National Key Lab of Autonomous Intelligent Unmanned Systems Beijing Institute of Technology School of Automation Beijing Institute of Technology

ISBN: (数字)9789887581581

ISBN: (纸本)9798350366907

This paper studies the time-optimal trajectory planning for manipulator. Conventional time-optimal trajectory planning utilizes the inverse solution, interpolation and intelligent optimization algorithms to search for the shortest time, making the process rather complex. To address this issue, we incorporate the kinematic equations and state transition equations into the existing two-stage algorithm used in unmanned aerial vehicles(UAVs), resulting in significantly improved computational speed and accuracy of the robotic arm's operation. The first stage predefines some resulting points related to path points and optimizes the robotic arm's kinematics and motion constraints as soft constraints to provide an initial solution for the second stage. In the second stage, based on the predetermined points of each trajectory segment provided by the first stage, the optimization problem is solved without the need for kinematic inverse solutions, in which the time intervals of each trajectory segment serve as optimization variables and the robotic arm's kinematics and motion constraints are used as hard constraints for optimization. Subsequently, the obtained joint points are interpolated using fifth-degree polynomials to form continuous joint trajectories. Comparative experiments with an improved particle swarm optimization algorithm verify that the proposed method exhibits higher optimization efficiency and achieves shorter optimized times.

关键词： Manipulator Time-Optimal Trajectory Planning two-stage algorithm Kinematics

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two-stage Multi-objective Optimization and Decision-making Method for Integrated Energy System Under Wind Generation Disturbances

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CSEE Journal of Power and Energy Systems 2024年第6期10卷 2564-2576页

作者： Bin Deng Xiaosheng Xu Mengshi Li Tianyao Ji Q.H.Wu School of Electric Power Engineering South China University of TechnologyGuangzhou 510640China

Although integrated energy systems(IES)are currently modest in size,their scheduling faces strong challenges,stemming from both wind generation disturbances and the system’s complexity,including intrinsic heterogeneity and pronounced *** this reason,a two-stage algorithm called the Multi-Objective Group Search Optimizer with Pre-Exploration(MOGSOPE)is proposed to efficiently achieve the optimal solution under wind generation *** optimizer has an embedded trainable surrogate model,Deep Neural Networks(DNNs),to explore the common features of the multiscenario search space in advance,guiding the population toward a more efficient search in each ***,a multiscenario Multi-Attribute Decision Making(MADM)approach is proposed to make the final decision from all alternatives in different wind *** reflects not only the decisionmaker’s(DM)interests in other indicators of IES but also their risk preference for wind generation disturbances.A case study conducted in Barry Island shows the superior convergence and diversity of MOGSOPE in comparison to other optimization *** respect to numerical performance metrics HV,IGD,and SI,the proposed optimizer exhibits improvements of 3.1036%,4.8740%,and 4.2443%over MOGSO,and 4.2435%,6.2479%,and 52.9230%over NSGAII,***’s more,the effectiveness of the multi-scenario MADM in making final decisions under uncertainty is demonstrated,particularly in optimal scheduling of IES under wind generation disturbances.

关键词： Decision making integrated energy systems(IES) two-stage algorithm wind generation disturbances

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A two-stage Approach for Electric Vehicle Routing Problem with Time Windows and Heterogeneous Recharging Stations

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Tsinghua Science and Technology 2024年第5期29卷 1300-1322页

作者： Tianyu Luo Yong Heng Lining Xing Teng Ren Qi Li Hu Qin Yizhi Hou Kesheng Wang School of Electronic Engineering Xidian UniversityXi’an 71007China Beijing Institute of Electronic System Engineering Beijing 100854China School of Logistics and Transportation Central South University of Forestry and TechnologyChangsha 410004China School of Management Huazhong University of Science and TechnologyWuhan 430074China School of River and Ocean Engineering Chongqing Jiaotong UniversityChongqing 400074China Department of Mechanical and Industrial Engineering Norwegian University of Science and TechnologyTrondheim 7491Norway

An Electric Vehicle(EV)is an appropriate substitution for traditional transportation means for diminishing greenhouse gas ***,decision-makers are beset by the limited driving range caused by the low battery capacity and the long recharging *** resolve the former issue,several transportation companies increases the travel distance of the EV by establishing recharging stations in various *** proposed Electric Vehicle-Routing Problem with Time Windows(E-VRPTW)and recharging stations are constructed in this context;it augments the VRPTW by reinforcing battery capacity ***,super-recharging stations are gradually emerging in the *** can decrease the recharging time for an EV but consume more energy than regular *** this paper,we first extend the E-VRPRTW by adding the elements of super-recharging *** then apply a two-stage heuristic algorithm driven by a dynamic programming process to solve the new proposed problem to minimize the travel and total recharging ***,we compare the experimental results of this approach with other algorithms on several sets of benchmark ***,we analyze the impact of super-recharging stations on the total cost of the logistic plan.

关键词： Electric Vehicle(EV) vehicle routing Dynamic Programming(DP) two-stage algorithm

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HCFS: A Density Peak Based Clustering algorithm Employing A Hierarchical Strategy

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IEEE ACCESS 2019年 7卷 74612-74624页

作者： Zhuo, Linlin Li, Kenli Liao, Bo Li, Hao Wei, Xiaohui Li, Keqin Hunan Univ Coll Comp Sci & Elect Engn Changsha 410008 Hunan Peoples R China Natl Supercomp Ctr Changsha 410082 Hunan Peoples R China SUNY Coll New Paltz Dept Comp Sci New Paltz NY 12561 USA

Clustering, which explores the visualization and distribution of data, has recently been widely studied. Although current clustering algorithms such as DBSCAN, can detect the arbitrary-shape clusters and work well, the parameters involved in these methods are often difficult to determine. Clustering using a fast search of density peaks is a promising technique for solving this problem. However, the current methods suffer from the problem of uneven distribution within local clusters. To solve this problem, we propose a new density peak based clustering algorithm employing a hierarchical strategy, namely, HCFS, which consists mainly of two stages. In the first stage, the HCFS estimates the density and distance of each point. The points with higher density and distance are selected as candidate centers, and then subclusters centered on them are further obtained. In the second stage, considering that adjacent subclusters based on certain candidate centers are highly similar and connected within the same cluster, we propose a new mechanism for measuring dissimilarity and connectivity between the subclusters. Those highly similar and connected subclusters are merged to increase the dissimilarity between different clusters and to obtain the final clustering results. The experiments conducted on a large number of datasets show that our method can effectively identify unevenly distributed clusters and yield better or comparable performance for different datasets.

关键词： Cluster candidate center density peak based hierarchical merge subclusters two-stage algorithm uneven distribution within local clusters

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Simplified searching for two defects

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JOURNAL OF STATISTICAL PLANNING AND INFERENCE 1998年第1期66卷 77-82页

作者： Macula, AJ Reuter, GR SUNY Geneseo Coll Geneseo Dept Math Geneseo NY 14454 USA Geneseo High Sch Dept Math Geneseo NY 14454 USA

In this paper, we discuss a nonadaptive group testing algorithm that identifies up to two defects. The number of required tests in our algorithm is not optimal, but our search procedure is less complex than that of other well known algorithms using fewer tests. We go on to discuss a simple two stage modification of our algorithm which dramatically reduces the number of sufficient tests. (C) 1998 Elsevier Science B.V.

关键词： separable matrices nonadaptive group testing parallel algorithm two-stage algorithm

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A novel two-stage discrete crack method based on the screened Poisson equation and local mesh refinement

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COMPUTATIONAL MECHANICS 2016年第6期58卷 1003-1018页

作者： Areias, P. Rabczuk, T. Cesar de Sa, J. Univ Evora Dept Phys Colegio Luis Antonio Verney Rua Romao Ramalho59 P-7002554 Evora Portugal Bauhaus Univ Weimar Inst Struct Mech Marienstr 15 D-99423 Weimar Germany Univ Porto Dept Mech Engn Fac Engn Rua Dr Roberto Frias S-N P-4200465 Oporto Portugal Univ Lisbon CERIS Inst Super Tecn Lisbon Portugal

We propose an alternative crack propagation algorithm which effectively circumvents the variable transfer procedure adopted with classical mesh adaptation algorithms. The present alternative consists of two stages: a mesh-creation stage where a local damage model is employed with the objective of defining a crack-conforming mesh and a subsequent analysis stage with a localization limiter in the form of a modified screened Poisson equation which is exempt of crack path calculations. In the second stage, the crack naturally occurs within the refined region. A staggered scheme for standard equilibrium and screened Poisson equations is used in this second stage. Element subdivision is based on edge split operations using a constitutive quantity (damage). To assess the robustness and accuracy of this algorithm, we use five quasi-brittle benchmarks, all successfully solved.

关键词： two-stage algorithm Local mesh refinement Smeared model Crack nucleation and propagation Quasi-brittle fracture

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Trivial two-stage group testing with high error rates

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JOURNAL OF COMBINATORIAL OPTIMIZATION 2003年第4期7卷 361-368页

作者： Macula, AJ SUNY Coll Geneseo Dept Math Geneseo NY 14454 USA

Given a population of cardinality q(r) that contains a positive subset P of cardinality p, we give a trivial two-stage method that has (((r+ 1)q)) - r ((q)(2)) first stage pools each of which contains q(r-2) objects. We assume that errors occur in the first stage. (2)We give an algorithm that uses the results of first stage to generate a set CP of candidate positives with |CP| less than or equal to (r + 1) q. We give the expected value of |CP boolean AND P|. At most (r + 1) q trivial second stage tests are needed to identify all the positives in CP. We assume that the second stage tests are error free.

关键词： group testing two-stage algorithm error-correcting nonadaptive non-adaptive

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Stochastic integration of demand response and reconfiguration in distribution network expansion planning

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IET GENERATION TRANSMISSION & DISTRIBUTION 2018年第20期12卷 4536-4545页

作者： Gouin, Victor Alvarez Herault, Marie-Cecile Raison, Bertrand Univ Grenoble Alpes CNRS Grenoble INP Inst EngnG2Elab F-38000 Grenoble France

Planning the distribution network of the future involves forecasting the most likely scenario to make appropriate investment decisions. Many uncertainties concerning, e.g. the evolution of conventional loads, renewable production and electric vehicles (EVs) make it difficult to predict the location of the distribution network's weaknesses (overvoltages, undervoltages and overcurrents) and their occurrence. In some cases, alternative solutions such as demand response (DR) and reconfiguration can remove the constraints and prevent expensive network investment. This study proposes a two-stage algorithm that is able to give the probability that no technical constraints will appear as a function of the reinforcement cost with and without using DR and/or reconfiguration. The first stage of the algorithm consists in running Monte Carlo simulations based on realistic scenarios for loads, EVs and renewable production development provided by French governmental roadmaps. The cost of reinforcement per line and per hour of constraints enables selection of the feeders, where DR (solved with linear programming) and/or reconfiguration (exhaustive research) will be implemented in the second stage of the algorithm to remove these constraints. The methodology is applied to a real part of a French distribution network.

关键词： linear programming power distribution planning power distribution economics distribution networks investment power generation planning Monte Carlo methods power transmission planning alternative solutions DR reconfiguration expensive network investment two-stage algorithm technical constraints reinforcement cost /or Monte Carlo simulations realistic scenarios EVs renewable production development French distribution network stochastic integration demand response distribution network expansion planning appropriate investment decisions conventional loads electric vehicles undervoltages overcurrents

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