检索结果-内蒙古大学图书馆

Multi-objective time-energy-impact optimization for robotic excavator trajectory planning

AUTOMATION IN CONSTRUCTION 2023年 156卷

作者： Feng, Hao Jiang, Jinye Ding, Nan Shen, Fangping Yin, Chenbo Cao, Donghui Li, Chunbiao Liu, Tao Xie, Jiaxue Nanjing Univ Informat Sci & Technol Sch Artificial Intelligence Nanjing 210044 Peoples R China Wuxi Cosmo Suspended Platform Co Ltd Wuxi 214128 Peoples R China Nanjing Univ Informat Sci & Technol Sch Comp Sci Nanjing 210044 Peoples R China Nanjing Univ Informat Sci & Technol Changwang Sch Honors Nanjing 210044 Peoples R China Nanjing Tech Univ United Inst Excavator Key Technol Nanjing 211816 Peoples R China SANY Grp Co Ltd Suzhou 215300 Peoples R China

Single-objective optimal trajectory cannot adapt to the complex requirements of excavator construction. A comprehensive optimal trajectory planning method is proposed to optimize the working time, energy consumption, and operational impact of robotic excavators. Without fusing any performance indexes, a normalized multi-objective function and an improved particle swarm optimization algorithm are established to achieve a comprehensive optimization of multiple objectives, while considering joint angle, velocity, acceleration, and quadratic acceleration constraints. Typical deep pit excavation simulation and experimental results show that the multi-objective optimization method is feasible, can balance multi-objective constraints, and can avoid falling into extremely long working times or large impacts. This method offers a more efficient and effective solution for multi-objective trajectory planning and provides a method for planning excavation trajectories based on different operating scenarios and objectives.

关键词： Excavator Hydraulic system Trajectory planning particle swarm optimization algorithm

来源：评论

学校读者我要写书评

暂无评论

A parameter determination method of unscented transformation and its approximate ability analysis in the precision estimation of nonlinear measurement adjustment

引用

MEASUREMENT 2020年 166卷 108065-108065页

作者： Wang, Leyang Ding, Rui East China Univ Technol Fac Geomat Nanchang 330013 Jiangxi Peoples R China Shandong Jianzhu Univ Sch Surveying & Geoinformat Jinan 250101 Peoples R China

Unscented transformation (UT) is the key technology of unscented Kalman filter, which can approximate probability distribution to estimate second-order approximate mean and covariance matrix of nonlinear function. In parameter selection of various sampling strategies in the framework of the unscented transformation (UT), there are few studies on the determination method of sampling parameters. In this study, the particle swarm optimization (PSO) algorithm is introduced into UT for high convergence efficiency and few control parameters. The parameter selection of several commonly used sampling strategies is analyzed from the numerical point of view, and a method to determine the sampling parameters is proposed. Furthermore, the higher-order information ignored by the recommended parameters of UT is considered, and the approximation ability of UT is tapped and improved by the obtained parameters. For the first time, the minimal skew simplex sampling (MSS) and the scaled minimal skew simplex sampling (SMSS) are applied to the precision estimation of nonlinear measurement adjustment. Considering the influence of non-normal distribution data on nonlinear error propagation in geodetic measurement, this study analyzes the PSO-UT model in a case study from the geodetic field. Experiments show that PSO can effectively determine the parameters of UT and improve its approximation ability, which enriches UT theory. (C) 2020 Elsevier Ltd. All rights reserved.

关键词： Nonlinear measurement adjustment Precision estimation Unscented transformation particle swarm optimization algorithm Parameter selection Non-normal distribution

来源：评论

学校读者我要写书评

暂无评论

Traveling wave inversion method of power line faults

引用

INTERNATIONAL JOURNAL OF ELECTRICAL POWER & ENERGY SYSTEMS 2023年第1期149卷

作者： Xia, Yixiang Li, Zewen Wang, Shuai Sun, Jian Guo, Xinyu Changsha Univ Sci & Technol Elect & Informat Engn Dept Changsha Peoples R China

In substations, the fault signal at the measuring point includes a variety of signal aliasing. This is partly due to the short length of the substation lines and the exitance of multiple types of equipment that cause the reflection and refraction of the traveling waves. Compared with the incident wave, the distortion in the fault signal is often significant hence interfering with the fault identification and location. To address this issue, we propose an inversion method of the incident wave. To do this, we first investigate the impact of multiple outlets of the substation bus, equivalent stray capacitance of the bus to the ground, transformers, line trap, and other types of equipment on traveling wave transmission. Modeling the aliasing effect of the traveling wave measuring point signal we then propose a fault signal filtering algorithm based on the improved Empirical Mode Decomposition (EMD) and Fast Fourier Transform (FFT). Using this algorithm we then formulate an incident wave inversion model based on substation component parameters. The component parameters in the equivalent circuit model of substation are then accurately identified to achieve an accurate inversion of the incident waves. Identification of parameters is based on an optimization model of substation component parameters based on the particle swarm optimization algorithm (PSO). Our results show that compared with the measured mixed wave signal, the fault characteristics of the inverted incident waves are more accurate, hence improving the fault location accuracy.

关键词： Waveform inversion Incident wave Substation particle swarm optimization algorithm

来源：评论

学校读者我要写书评

暂无评论

Cooperative-driving control for mixed fleets at wireless charging sections for lane changing behaviour

引用

ENERGY 2022年第0期243卷 122976-122976页

作者： Li, Bin Dong, Xujun Wen, Jianghui Changan Univ Sch Automobile Xian 710064 Shaanxi Peoples R China Wuhan Univ Technol Sch Sci Wuhan 430063 Peoples R China

Recently, electric vehicles (EVs) have become an important traffic tool in connected and automated environments due to their own advantages. However, the optimal driving control strategies of EVs and charging modes of wireless charging lanes are complex since wireless charging technology is limited when EVs are moving and traffic conditions are random. This paper constructs a scenario in which wireless charging facilities are deployed in part of a single lane and proposes a cooperative control method of mixed fleets including EVs and fuel vehicles based on the four objectives of driving safety, traffic efficiency, passenger comfort and energy management. Combined with the particle swarm optimization algorithm, the average driving velocity, lane-changing frequency and location of vehicles under different deployment lengths of charging facilities and mixing ratios are compared to discuss the influence of deployment length on the control effect of energy consumption and traffic efficiency. The numerical results indicate that when the lane length is 1500 m, with the increasing proportion of EVs, the optimal deployment lengths are approximately 700 m, 550 m and 400 m in the case of low traffic density and approximately 550 m, 500 m and 450 m in the case of high traffic density.(c) 2022 Elsevier Ltd. All rights reserved.

关键词： Cooperative control method of mixed fleet particle swarm optimization algorithm Optimal deployment Energy consumption

来源：评论

学校读者我要写书评

暂无评论

Fast basis search for adaptive Fourier decomposition

引用

EURASIP JOURNAL ON ADVANCES IN SIGNAL PROCESSING 2018年第1期2018卷 1页

作者： Wang, Ze Wan, Feng Wong, Chi Man Qian, Tao Univ Macau Dept Elect & Comp Engn Fac Sci & Technol Ave Univ Taipa Macau Peoples R China Univ Macau Dept Math Fac Sci & Technol Ave Univ Taipa Macau Peoples R China

The adaptive Fourier decomposition (AFD) uses an adaptive basis instead of a fixed basis in the rational analytic function and thus achieves a fast energy convergence rate. At each decomposition level, an important step is to determine a new basis element from a dictionary to maximize the extracted energy. The existing basis searching method, however, is only the exhaustive searching method that is rather inefficient. This paper proposes four methods to accelerate the AFD algorithm based on four typical optimization techniques including the unscented Kalman filter (UKF) method, the Nelder-Mead (NM) algorithm, the genetic algorithm (GA), and the particle swarm optimization (PSO) algorithm. In the simulation of decomposing four representative signals and real ECG signals, compared with the existing exhaustive search method, the proposed schemes can achieve much higher computation speed with a fast energy convergence, that is, in particular, to make the AFD possible for real-time applications.

关键词： Adaptive Fourier decomposition Unscented Kalman filter Nelder-Mead algorithm Genetic algorithm particle swarm optimization algorithm

来源：评论

学校读者我要写书评

暂无评论

Evolutionary dynamics in spatial threshold public goods game with the asymmetric return rate mechanism

引用

CHAOS SOLITONS & FRACTALS 2020年 136卷 109819-109819页

作者： Wang, Xianjia Chen, Wenman Wuhan Univ Econ & Management Sch Wuhan 430070 Peoples R China Wuhan Univ Inst Syst & Engineer Wuhan 430070 Peoples R China

In reality, cooperators often are provided a higher return rate for their contributions. Inspired by the reality, this paper introduces the asymmetric return rate mechanism, where the return rate is asymmetric between cooperators and defectors. This paper mainly studies how the asymmetric return rate mechanism influences the evolutionary dynamics in spatial threshold public goods game on two different complex networks, the namely square lattice and Barabási-Albert scale-free network. The simulation results show that increasing the sensitivity for the spread of cooperation is more effective than increasing that for the spread of defection not only to promote cooperation, but also to elevate the provision of the public goods. In addition, a moderate value of threshold is the best to elevate both the promotion of cooperation and the provision of the public goods.

关键词： Evolutionary dynamics Spatial threshold public goods game Asymmetric return rate particle swarm optimization algorithm

来源：评论

学校读者我要写书评

暂无评论

A tristable nonlinear energy sink

引用

INTERNATIONAL JOURNAL OF MECHANICAL SCIENCES 2023年 238卷

作者： Zeng, You-cheng Ding, Hu Shanghai Univ Shanghai Inst Appl Math & Mech Sch Mech & Engn Sci Shanghai Key Lab Mech Energy Engn Yangchang Rd 149189 Shanghai 200444 Peoples R China

The tristable characteristics are mostly used in the field of energy harvesting and vibration isolator, but are rarely devoted to in the field of vibration absorption. In this paper, a tristable nonlinear energy sink (TNES) model is proposed for vibration absorption. The TNES is constructed by fixing a magnet in the middle of the clamping pre -pressure beam, and setting a magnet on both sides of the fixed magnet. By adjusting the magnet position, the proposed TNES can be transformed into bistable NES (BNES) and monostable NES (MNES). The TNES is coupled with the linear oscillator (LO), and the differential equation of motion of the coupled system is obtained with the Hamiltonian principle. The approximate analytical method and the numerical method are mutually verified. The vibration reduction efficiency of the TNES under harmonic excitation is presented. The influence of the pa-rameters of the TNES on the dynamics and vibration reduction efficiency is studied. The optimal parameters of the TNES are obtained by the particle swarm optimization (PSO) algorithm. Compared with the corresponding bistable NES and monostable NES, it shows that the tristable NES has obvious advantages in vibration sup-pression efficiency. The effects of the TNES barrier depths and the excitation amplitude on the vibration reduction efficiency are revealed. The TNES can dissipate energy through chaotic inter-well oscillation between three stable positions, and achieve the purpose of effectively suppressing vibration.

关键词： Nonlinear energy sink Tristable Vibration control Harmonic balance method particle swarm optimization algorithm

来源：评论

学校读者我要写书评

暂无评论

Wavefront sensing method for diffraction optical system based on phase diversity

引用

INFRARED PHYSICS & TECHNOLOGY 2019年 102卷 102980-000页

作者： Zhi, Xiyang Gong, Jinnan Yu, Di Wang, Dawei Niu, Ruize Harbin Inst Technol Res Ctr Space Opt Engn Harbin 150001 Heilongjiang Peoples R China

In this paper, we present a novel wavefront sensing method for diffraction optical system based on phase diversity. Based on the physical-imaging mechanism of diffractive optical system, the wavefront characteristics of the diffraction optical system are characterized by using diffraction efficiency. On this basis, a novel modified phase diversity (PD) wavefront sensing method is established based on the blocking idea. After that, the global optimization method of corresponding method based on particle swarm optimization algorithm is proposed. Finally, some experiment results are achieved with the experiment on a membrane diffraction optical system. Experimental results indicate that the proposed algorithm performs well on both wavefront reconstruction and image restoration and is far superior to traditional methods in diffraction optical systems. The accuracy of our proposed PD method is at least two orders of magnitude higher than the traditional method. Taking the 0.01 degrees field of view for example, our modified PD method can achieve the accuracy of 2.5 x 10(-4) wavelength when the diffraction efficiency is higher than 0.6. This proposed method can be applied to improve the image quality of the diffraction optical system and further support the on-orbit application of ultra-large aperture membrane imaging technology.

关键词： Wavefront sensing Phase diversity Diffraction optical system particle swarm optimization algorithm

来源：评论

学校读者我要写书评

暂无评论

Spatial accessibility analysis and location optimization of emergency shelters in Deyang

引用

GEOMATICS NATURAL HAZARDS & RISK 2023年第1期14卷

作者： Zhang, Zuopei Hu, Yunfeng Lu, Wei Cao, Wei Gao, Xing Chinese Acad Sci Inst Geog Sci & Nat Resources Res State Key Lab Resources & Environm Informat Syst Beijing Peoples R China Univ Chinese Acad Sci Coll Resources & Environm Beijing Peoples R China

The selection and planning of the location of emergency shelters have a crucial impact on the safety of residents and cities. In this paper, based on multivariate open geographic data, the Gaussian two-step floating catchment area method, K-means clustering, and particle swarm optimization algorithm methods are utilized to carry out a spatial accessibility analysis and location optimization of emergency shelters in Deyang City, Sichuan Province, China. The study shows that: (1) Deyang City's emergency shelters are higher than the government's relevant standard requirements in terms of major indicators such as single building area, total area and per capita shelter area. (2) The spatial distribution of emergency shelters in the study area is uneven and unreasonable, with accessibility from the urban center outwards, exhibiting a "high-low" distribution pattern. (3) The study suggests that 10 new emergency shelters can reduce the number of accessible blind areas by 43.31%. The study recommends that the assessment and construction of emergency shelter facilities in rural areas in China and globally should be emphasized. Reliable recommendations for improvement of emergency shelter planning in Deyang city are provided in the study results.

关键词： Spatial accessibility Gaussian two-step floating catchment area method K-means clustering particle swarm optimization algorithm location optimization

来源：评论

学校读者我要写书评

暂无评论

optimization control of hydrometallurgical leaching process based on IDE-MPC

引用

MINERALS ENGINEERING 2022年第0期176卷 107341-107341页

作者： Niu, Dapeng Liu, Xudong Liu, Yuanqing Jia, Mingxing Northeastern Univ Coll Informat Sci & Engn Shenyang Peoples R China

The utilization rate of raw materials during the hydrometallurgical leaching process has a great influence on the whole economic benefits of the hydrometallurgy plant, so it is necessary for the leaching process to improve the utilization of materials using optimization control methods. In this paper, the dynamic model for the hydrometallurgical leaching process of a gold hydrometallurgy plant is first built based on the reaction mechanism of the process. Then, the model parameters are identified using least-squares fitting. Thereafter, with the maximum economic benefit as the objective function, the steady-state economic optimization model of the leaching process is established, and an improved particle swarm optimization algorithm is used to solve the model. Taking the optimization results as the control objective, a model predictive control method based on an improved differential evolution algorithm is proposed to control the leaching process, so as to improve the intractability and anti-disturbance performance of the controller for the leaching process. The simulation results show that the proposed optimization and control methods achieve satisfactory effects.

关键词： Hydrometallurgical leaching process optimization control particle swarm optimization algorithm Model predictive control Differential evolution algorithm

来源：评论

学校读者我要写书评

暂无评论

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案：

请选择收藏分类：

通借通还

建议与咨询 留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案： 新增检索档案 确定 取消

请选择收藏分类： 新增自定义分类 确定 取消

通借通还

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

请选择保存的检索档案：

请选择收藏分类：