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Trajectory Planning in Joint Space for a Pointing Mechanism Based on a Novel Hybrid Interpolation algorithm and nsga-ii algorithm

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IEEE ACCESS 2020年 8卷 228628-228638页

作者： Sun, Jing Han, Xueyan Zuo, Yaming Tian, Shaoqian Song, Jingwei Li, Shihua Yanshan Univ Parallel Robot & Mechatron Syst Lab Hebei Prov Qinhuangdao 066004 Hebei Peoples R China

In order to improve the motion stability of a pointing mechanism, the trajectory planning and trajectory optimization were conducted. To obtain better motion stability, the jerk is required continuous. Therefore, higher order polynomial or B-spline are needed and the calculation amount increases in trajectory planning. A novel hybrid interpolation algorithm "7-order polynomial + improved quartic uniform B-spline curve + 7-order polynomial" was proposed for trajectory planning, which cannot only ensure the trajectory passes through all path points but also ensure the jerk is continuous. From the first path point to the second path point and from the penultimate path point to the last path point, 7-order polynomial is chosen as the interpolation algorithm. The intermediate path points are interpolated by improved quartic uniform B-spline curve which is newly proposed. The improved quartic uniform B-spline curve can pass through all path points and does not require complicated calculation. To carry out the trajectory planning of a X-Y pointing mechanism, the kinematic model was derived at first. Secondly, the hybrid interpolation algorithm was presented. Thirdly, the nsga-ii algorithm was applied to the multi-objective optimization which are time, acceleration and jerk. Finally, the trajectory planning experiment was conducted to prove the validity of the proposed hybrid interpolation algorithm. The experimental results show that the pointing accuracy is improved by using the hybrid interpolation algorithm and the nsga-ii algorithm. This hybrid interpolation algorithm for trajectory planning can be applied to other robots as well.

关键词： Trajectory planning Interpolation Splines (mathematics) Robots Kinematics Planning End effectors Hybrid interpolation algorithm improved quartic uniform B-spline curve trajectory planning and optimization in joint space nsga-ii algorithm pointing mechanism

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DESIGN OF NEW CLEAN AND EFFICIENT COMBUSTION MODE AND THERMODYNAMICS RESEARCH USING nsga-ii algorithm

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THERMAL SCIENCE 2020年第5期24卷 2699-2706页

作者： Shen, Guoqing Hangzhou Vocat & Tech Coll Automobile Coll Hangzhou Zhejiang Peoples R China

In order to study a new clean and efficient combustion mode, which can relieve the pressure of traditional energy and ensure low emissions, in this study, a diesel/natural gas dual fuel engine is designed by non-dominant sorting genetic algorithm (nsga-ii), and its thermodynamic characteristics are studied. The WP 10.290 Diesel engine is modified into a diesel/natural gas dual fuel engine. The emissions of harmful substances and thermal efficiency of the modified engine under different working conditions are compared. The combustion chamber structure and adaptability between combustion chamber and injection parameters are optimized by using nsga-ii algorithm and CFD software. The results show that the emission of NOx and CH4 and the fuel consumption rate can be reduced simultaneously by using the composite combustion model compared with the original engine. When the CH4 emission is close to zero, the fuel consumption rate decreases obviously, and NOx slightly increases. When the angle between the injection holes is 141.57 degrees, the amount of NOx in the cylinder is large. When the injection advance angle is 21.91 degrees CA, the pressure in the cylinder is the highest, the CH4 production is the lowest, the NOx production is higher, and the oxygen content in the combustion mixture is less. The NOx production is the lowest. diesel/natural gas dual fuel engine can ensure efficient combustion while reducing emissions. In this study, the performance of the dual fuel engine at various speeds can be further studied, which can provide theoretical support for the design of diesel/natural gas dual fuel engine.

关键词： diesel/natural gas dual fuel engine nsga-ii algorithm CFD pollutant emissions

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Optimization of Variable Blank Holder Force Based on a Sharing Niching RBF Neural Network and an Improved nsga-ii algorithm

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INTERNATIONAL JOURNAL OF PRECISION ENGINEERING AND MANUFACTURING 2019年第2期20卷 285-299页

作者： Xie, Yanmin Tang, Wei Zhang, Fei Pan, BeiBei Yue, Yaopeng Feng, Meiqiang Southwest Jiaotong Univ Sch Mech Engn 111 North 1st Sect Second Ring Rd Chengdu 610031 Sichuan Peoples R China

Variable blank holder force (VBHF) is an important process parameter in sheet metal forming. The purpose of this study is to propose a sharing niching radial basis function (SNRBF) neural network for VBHF optimization. Two methods are put forward to improve the prediction accuracy of a RBF neural network. (1) A RBF neural network is trained by a sharing niching technique to achieve global optimal nodes. (2) In Latin hypercube design, Spearman correlation analysis is employed to decrease sample correlation. In addition, in order to improve the performance of the non-dominated sorting genetic algorithm (nsga-ii), excellent individuals in each class of non-dominated individuals are selected by employing immune operators. Based on the Spearman correlation analysis and the Latin hypercube method, training samples are generated and numerical simulations are performed for a double C part. The surrogate models between VBHF and forming quality are constructed by a SNRBF neural network. The Pareto frontier solutions are achieved by employing the improved nsga-ii algorithm. Grey relational analysis is applied to determine the optimal VBHF loading trajectory. The results show decreased wrinkles in the optimized forming part and greater uniformity in the plastic deformation by employing the optimized VBHF, thereby leading to improvement in the forming quality of the double C. [GRAPHICS] .

关键词： Variable blank holder force Sharing niching technique RBF neural network Spearman correlation analysis nsga-ii algorithm Grey relational analysis

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Geometrical optimization of solar venetian blinds in residential buildings to improve the economic costs of the building and the visual comfort of the residents using the nsga-ii algorithm

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INTERNATIONAL COMMUNICATIONS IN HEAT AND MASS TRANSFER 2024年 157卷

作者： Liu, Jie Baghoolizadeh, Mohammadreza Basem, Ali Hamza, Hussein Sudhamsu, Gadug Al-Musawi, Tariq J. Sultan, Abbas J. Salahshour, Soheil Alizadeh, A. Yanan Univ Coll Chem & Chem Engn Yann 716000 Shaanxi Peoples R China Shahrekord Univ Dept Mech Engn 88186-34141 Shahrekord Iran Warith Al Anbiyaa Univ Fac Engn Karbala 56001 Iraq Al Amarah Univ Coll Dept Engn Tech Mech Power Maysan Iraq JAIN Sch Engn & Technol Dept Comp Sci & Engn Bangalore Karnataka India Al Mustaqbal Univ Coll Bldg & Construct Tech Engn Dept Babylon 51001 Iraq Univ Technol Iraq Dept Chem Engn Baghdad Iraq Istanbul Okan Univ Fac Engn & Nat Sci Istanbul Turkiye Bahcesehir Univ Fac Engn & Nat Sci Istanbul Turkiye Lebanese Amer Univ Dept Comp Sci & Math Beirut Lebanon Urmia Univ Coll Engn Dept Mech Engn Orumiyeh Iran

The entering sunlight from the building's windows mainly affects the heating and visual comfort of the occupants. The applications of Venetian blinds are a solution to improve the heating and visual comfort of the occupants. However, reducing the sunlight that enters the space can result in a rise in the building's electricity consumption. While most studies focus on the electricity production of solar panels, present study aims to examine the effect of solar venetian blinds on the indoor visual and thermal comfort of the occupants and optimize their geometry considering different geographical specifications. In the present paper, efforts are made to numerically install solar panels on Venetian blinds and analyze the effect of changing the geometrical parameters of solar Venetian blinds and the building's window dimensions on visual comfort and net electricity. Therefore, the target functions in the present paper are an improvement percentage in the daylight glare index and an improvement percentage in the net electricity costs for the analyzed building. As a result, five cities in Iran that have different climatic conditions are targeted to model the building. EnergyPlus software is employed to conduct the energy-based calculations, and the design variables and target functions are defined using JEPLUS software. The outputs are next inserted in JEPLUS+EA software to process a multi-objective optimization using the nsga-ii algorithm. The results demonstrate that the visual comfort and net electricity can be optimized by ranges of 10-100% and 1.5-10%, respectively. Furthermore, Venetian blinds are proven to have higher reception of sun radiations and better efficiency in southern cities and they can have a more proper performance while being installed for windows of southern building wall.

关键词： Solar venetian blinds Multi -objective optimization nsga-ii algorithm Visual comfort Annual electricity costs

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Research on Multi-objective Optimization Model of Power Storage Materials Based on nsga-ii algorithm

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INTERNATIONAL JOURNAL OF COMPUTATIONAL INTELLIGENCE SYSTEMS 2024年第1期17卷 1-13页

作者： Hu, Zixi Liu, Shuang Yang, Fan Geng, Xiaodong Huo, Xiaodi Liu, Jia State Grid Hebei Elect Power Co Ltd Shijiazhuang Power Supply Branch Shijiazhuang 050000 Hebei Peoples R China State Grid Hebei Elect Power Co Ltd Shijiazhuang 050000 Hebei Peoples R China State Grid Shijiazhuang Luancheng Dist Elect Power Hengshui 051430 Hebei Peoples R China State Grid Pingshan Elect Power Supply Co Tianjin 050400 Hebei Peoples R China

Aiming at the problems of slow convergence speed and low precision probability of multi-objective optimization of energy storage materials, a multi-objective optimization model of energy storage materials based on nsga-ii algorithm was proposed. The association rule set of storage materials in the joint supply chain operation performance management system is extracted, and the rough vector feature distribution set multi-objective optimization method is used to decompose and optimize the characteristics of storage materials in the joint supply chain operation performance management system. Using nsga-ii optimization analysis method, this paper summarizes the power storage materials under the joint supply chain operation performance management system, and summarizes three kinds of inventory control: periodic inventory, inventory coding, and computerized inventory. Combined with the positive regression learning method of organizational operational performance, the multi-objective optimization decision of electric storage materials under the joint supply chain operational performance management system is realized. The simulation results show that under the joint supply chain operation performance management system, the proposed method reaches the optimal convergence after 65 iterations, the convergence speed is fast, and the accuracy probability reaches 1.000 after 80 iterations, which solves the problems of slow convergence speed and low accuracy probability, and has a good scheduling ability of energy storage materials.

关键词： nsga-ii algorithm Electric power storage materials Multi-objective optimization Rough vector Joint supply chain Operational performance management

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Multi-objective optimal design of permanent magnet eddy current retarder based on nsga-ii algorithm

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ENERGY REPORTS 2022年 8卷 1448-1456页

作者： Niu, Bowen Wang, Dazhi Pan, Pengyi Northeastern Univ Coll Informat Sci & Engn 3-11 Wenhua Rd Shenyang 110819 Peoples R China

As a new type of vehicle auxiliary braking device, permanent magnet eddy current retarder has a wide application prospect. In this paper, the linear layer analysis method and non-dominated sorting genetic algorithm-ii (nsga-ii) are combined to optimize the parameters of permanent magnet eddy current retarder. Firstly, based on the linear layer model, the mathematical optimization model of permanent magnet eddy current retarder is established by taking the radial length of permanent magnet, the thickness of permanent magnet, the number of permanent magnets and the thickness of conductor disk as design variables, the braking torque and eddy current loss as optimization objectives. Secondly, the nsga-ii algorithm is used to optimize the braking torque and eddy current loss of the permanent magnet eddy current retarder. Finally, the performance of the permanent magnet eddy current retarder after the optimization of the structural parameters is carried out by using ANSYS software to verify the accuracy and feasibility of the optimization results. The optimization algorithm used in this article solves the problem of poor adaptability to environmental changes and premature convergence in the late evolution of standard genetic algorithm. The results show that the nsga-ii algorithm based on the layer analysis model has better computational results in the optimal design of structural parameters than the standard genetic algorithm. (C) 2021 Published by Elsevier Ltd.

关键词： Permanent magnet eddy current retarder Multi-objective optimization Linear layer model nsga-ii algorithm ANSYS

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Thermo-economical modeling and multi-objective optimization of thermal energy driven multiple effect distillation system for water treatment using nsga-ii algorithm

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DESALINATION AND WATER TREATMENT 2024年 320卷

作者： Chandra, Pravesh Mudgal, Anurag Patel, Jatin Patel, Vivek Kumar Moradabad Inst Technol Moradabad 244001 India Pandit Deendayal Energy Univ Sch Technol Gandhinagar 382426 India

This study presents a thermoeconomic model for optimizing the operation of a Multiple Effect Distillation (MED) system driven by thermal energy. By evaluating configurations with 2-, 4-, and 6-effects, the research aims to enhance distillate output (DO) while minimizing the Cost of Distillate (COD). Key parameters such as motive steam flow rate, steam pressure, and feed water temperature are investigated to determine their impact on system performance. Comparative analysis reveals significant increases in distillate output with additional effects, notably a 27 % rise with 4 effects and a further 34 % increase with 6 effects. Moreover, as the number of effects increases, there is a corresponding elevation in the minimum operating pressure of motive steam, narrowing the operating pressure range. The study identifies the 6-effect MED system as the optimal configuration, balancing thermal efficiency and economic feasibility by offering a wider range of steam flow rates while minimizing operating pressure. Furthermore, the research highlights the importance of maintaining an optimal feedwater temperature of 80 0C to avoid reduced distillate output and increased COD.

关键词： Desalination Multi effect distillation Modelling Multi-objective optimization Thermoeconomic analysis nsga-ii algorithm

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Optimisation configuration of hybrid AC/DC microgrid containing electric vehicles based on the nsga-ii algorithm

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JOURNAL OF ENGINEERING-JOE 2019年第10期2019卷 7229-7236页

作者： Ye, Bin Shi, Xuemei Wang, Xuli Wu, Hongbin State Grid Anhui Econ Res Inst Hefei 230022 Anhui Peoples R China Hefei Univ Technol Sch Elect Engn & Automat Hefei 230009 Anhui Peoples R China

Based on the development of hybrid AC/DC microgrid, considering the objectives of microgrid life-cycle cost, self-balancing rate and converter losses, an optimisation configuration model of a hybrid AC/DC microgrid is established here. Based on the different model of EVs to connect with grid, the matching control strategies for the model are proposed. The elitist non-dominated sorting genetic algorithm (nsga-ii) is applied to solve the optimisation configuration model. With the example system simulation, the demand response function of EVs is analysed, and the impacts of different EVs charging modes on optimisation configuration results of the hybrid AC/DC microgrid are studied and discussed. The rationality and effectiveness of proposed models and strategies are verified.

关键词： Pareto optimisation distributed power generation electric vehicles genetic algorithms hybrid AC/DC microgrid microgrid life-cycle cost optimisation configuration model optimisation configuration results electric vehicles nsga-ii algorithm self-balancing rate converter losses matching control strategies non-dominated sorting genetic algorithm demand response function EV charging modes

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Multi-Objective Optimum Design for Wave-Plate Demister Based on nsga-ii algorithm

Multi-Objective Optimum Design for Wave-Plate Demister Based...

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3rd International Conference on Energy, Environment and Sustainable Development (EESD 2013)

作者： Qiao, Zongliang Zhang, Lei Si, Fengqi Xu, Zhigao Southeast Univ Sch Energy & Environm Nanjing Jiangsu Peoples R China Nanjing Coll Chem Technol Dept Mech Technol Nanjing Peoples R China

ISBN: (纸本)9783037859735

For optimizing the structure design of the wave-plate demister vanes in wet flue gas desulfurization system (WFGD) of power plants, the characteristics models of removal efficiency and pressure drop were established by using least squares support vector machine (LSSVM) based on numerical simulation results. The highest relative error between the predicted output and measured value is 2%, it proves the modeling is good for the prediction. Based on the characteristics models, a multi-objective optimization model was established. It used the structural parameters as the optimal variables and the demister characteristics as the objective function. This optimization model was solved by non dominated sorting genetic algorithm (nsga-ii). The simulation data show that the Multi-objective optimum method can get more effective results compared to the weight coefficient method.

关键词： demister removal efficiency pressure drop LSSVM nsga-ii algorithm

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Multi-Objective Network Coding Optimization Based On nsga-ii algorithm

Multi-Objective Network Coding Optimization Based On NSGA-II...

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International Conference on Control Engineering and Communication Technology (ICCECT)

作者： Hao, Kun Wang, Beibei Luo, Yongmei Tianjin Inst Urban Construct Sch Comp & Informat Engn Tianjin Peoples R China Tianjin Inst Urban Construct Sch Control & Mech Engn Tianjin Peoples R China Tianjin Univ Sch Comp Sci & Technol Tianjin Peoples R China

ISBN: (纸本)9781467344999;9780769548814

Network coding could effectively improve transmission performance of multicast network, but encoding of node brings the additional calculation cost of node. In order to overcome the overhead brought by network coding, a network coding optimization model under the framework of algebraic network coding is designed in this paper, and the joint optimization for both the link cost and coding cost of network coding are carried out based on this model. In addition, the paper proposes MOONC (Multi-Objective Optimization Problem of Network Coding) based on improved nsga-ii algorithm. Adopting non-dominated sorting mechanism, virtual fitness and elitist strategy, this algorithm could not only improve algorithm efficiency and convergence speed, but also guarantee the population diversity. The simulation for typical network topology shows that this algorithm is effective and feasible.

关键词： Network Coding Link Cost Coding Cost nsga-ii algorithm

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