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A New Method for Solving objective function of Hybrid Electric Propulsion System for Intelligent Design

IEEE TRANSACTIONS ON TRANSPORTATION ELECTRIFICATION 2024年第2期10卷 3043-3060页

作者： Yan, Zhi-Wei Wang, Biao Ju, Ting Chen, Wei Nanjing Univ Aeronaut & Astronaut Coll Energy & Power Engn Nanjing 210016 Peoples R China Nanjing Univ Aeronaut & Astronaut Coll Automat Engn Nanjing 210016 Peoples R China Chongqing Jiaotong Univ Inst Aeronaut Chongqing 400074 Peoples R China

Using hybrid electric propulsion system (HEPS) is one of the ways to reduce aircraft environmental pollution and help to bring the airlines into the all-electric era. However, the objective function of aircraft HEPS for intelligent search design is relatively simple at present. In this article, a new method for solving the objective function of HEPS intelligent design was proposed, which solves the problem of poor accuracy of power level modeling and improves the ability to explore global optimal results. This article took the fixed-wing unmanned aerial vehicle that mainly performs long-range flight tasks as an example. The load curve solving methods were compared, and the entire calculation structure was optimized for computational efficiency. Also, the results of more than 13% fuel saving rate with high fuel efficiency compared with pure fuel-powered flight were obtained. The combination of energy management strategy (EMS) participation in load curve solving and further dynamic programming (DP) optimization in objective function solving was proved to be optimal.

关键词： Autonomous aerial vehicles Atmospheric modeling Energy management Aircraft Mathematical models Linear programming Batteries Energy management strategy (EMS) hybrid electric propulsion system (HEPS) objective function

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A least third-order cumulants objective function

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NEURAL PROCESSING LETTERS 1996年第2期3卷 91-99页

作者： Leung, CT Chow, TWS Yam, YF CITY UNIV HONG KONG DEPT ELECT ENGNKOWLOONHONG KONG

A novel Least Cumulants Method is proposed to tackle the problem of fitting to underlying function in small data sets with high noise level because higher-order statistics provide an unique feature of suppressing Gaussian noise processes of unknown spectral characteristics. The current backpropagation algorithm is actually the Least Square Method based algorithm which does not perform very well in noisy data set. Instead, the proposed method is more robust to the noise because a complete new objective function based on higher-order statistics is introduced. The proposed objective function was validated by applying to predict benchmark sunspot data and excellent results are obtained. The proposed objective function enables the network to provide a very low training error and excellent generalization property. Our results indicate that the network trained by the proposed objective function can, at most, provide 73% reduction of normalized test error in the benchmark test.

关键词： Least Cumulants Method third-order cumulants objective function least cumulants based backpropagation

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Required relationship between objective function and Pareto frontier orders: Practical implications

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AIAA JOURNAL 2001年第11期39卷 2168-2174页

作者： Messac, A Ismail-Yahaya, A Rensselaer Polytech Inst Dept Mech Engn Aeronaut Engn & Mech Multidisciplinary Design & Optimizat Lab Troy NY 12180 USA

It is well known that the weighted sum aggregate objective function fails to capture Pareto points that are located on a concave region of the Pareto frontier. Conditions are established for a general aggregate objective function to capture points on a concave Pareto frontier region. Specifically, these conditions are developed in terms of the relative orders of the Pareto frontier and aggregate objective function. These critical conditions can be used in practice to allow an aggregate objective function to capture any potentially desirable Pareto point. Conversely, failure to satisfy these critical conditions can represent a pivotal failure point of the general application of design optimization because we may fail to obtain the design we seek.

关键词： .capture objective function aggregate objective Required Relationship Frontier Orders Practical Implications concave Pareto

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The Influence of objective function and Acceptability Threshold on Uncertainty Assessment of an Urban Drainage Hydraulic Model with Generalized Likelihood Uncertainty Estimation Methodology

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WATER RESOURCES MANAGEMENT 2015年第6期29卷 2059-2072页

作者： Zhang, Wei Li, Tian Tongji Univ State Key Lab Pollut Control & Resource Reuse Shanghai 200092 Peoples R China

Urban drainage model is an important computer-aided tool in stormwater management and drainage planning and designing. A popular urban drainage hydraulic model, stormwater management model (SWMM), was applied in a pump lifting combined sewer system for a high-intensity urban catchment located in Shanghai, China. Uncertainty of SWMM water quantity parameters was assessed with generalized likelihood uncertainty estimation (GLUE) methodology. The sensitivity of parameters was discussed and compared based on the results of uncertainty analysis. To discuss the influence of the acceptability threshold on model parameter sensitivity and the margin of uncertainty band, the GLUE approach was applied several times varying acceptability threshold. The results indicated that a higher acceptability threshold value is contributed to achieve a stricter verification with a high confidence level, and the uncertainty analysis significant level can be featured by the value of acceptability threshold. The selection of acceptability threshold value can be regarded as a tradeoff process. Both reducing the low efficient simulation and reducing computation cost should be considered for the selection of acceptability threshold. Moreover, the GLUE approach was applied several times varying different objective functions with corresponding acceptability thresholds. The results indicated that some parameters may be sensitive to a specific objective function, and other parameters may be sensitive to another objective function. Some parameters cannot easily identified when a single objective function was used within the GLUE approach, and a multiple-objective function combined different objective functions requirements, may be a alternative approach to reduce the model prediction uncertainty.

关键词： Combined sewer system objective function Acceptability threshold Uncertainty analysis Stormwater management model (SWMM) Generalized likelihood uncertainty estimation (GLUE)

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A Fault Diagnosis Method of Power Systems Based on Improved objective function and Genetic Algorithm-Tabu Search

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IEEE TRANSACTIONS ON POWER DELIVERY 2010年第3期25卷 1268-1274页

作者： Lin, Xiangning Ke, Shuohao Li, Zhengtian Weng, Hanli Han, Xionghui Huazhong Univ Sci & Technol Elect Power Secur & High Efficiency Lab Wuhan 430074 Peoples R China

Based on the improved optimization objective function of fault diagnosis, a genetic algorithm-Tabu search (GATS) method is introduced for the purpose of fault diagnosis of power systems. The genetic algorithm has good global search ability, while the Tabu search algorithm has good local search ability. Integrating the advantages of these two algorithms, a new hybrid algorithm, called GATS, can be obtained. Using the function of Shcaffer, the advantages of GATS are proven in this paper. The results of case studies show that GATS is superior to conventional methods in terms of the sensitivity of original solution and the dependency of original parameters. The satisfactory results can be obtained when the GATS method is applied in the event of abnormal operations of protective relays and circuit breakers or the multiple-fault scenarios.

关键词： Fault diagnosis genetic algorithm (GA) genetic algorithm-Tabu search (GATS) objective function Tabu search

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An objective function to Evaluate Performance of Human-Robot Collaboration in Target Recognition Tasks

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IEEE TRANSACTIONS ON SYSTEMS MAN AND CYBERNETICS PART C-APPLICATIONS AND REVIEWS 2009年第6期39卷 611-620页

作者： Bechar, Avital Meyer, Joachim Edan, Yael ARO Inst Agr Engn IL-50250 Bet Dagan Israel Ben Gurion Univ Negev Dept Ind Engn & Management IL-84105 Beer Sheva Israel

Robotic systems in unstructured environments must cope with unknown, unpredictable, and dynamic situations. Inherent uncertainty, and limited sensor accuracy and reliability impede target recognition performance. Introducing a human operator into the system can help improve performance and simplify the robotic system. In this paper, four basic levels of collaboration were defined for human-robot collaboration in target recognition tasks. An objective function that includes operational and time costs was developed to quantify performance and determine the best collaboration level. Signal detection theory was applied to evaluate system performance. The optimal collaboration level for different cases was determined by using numerical analyses of the objective function. The findings indicate that the best system performance, the optimal values of performance measures, and the best collaboration level depend on the task, the environment, human and robot parameters, and the system characteristics. For the tested cases, the manual level was never the best collaboration level for achieving the optimal solution. The autonomous level was the best collaboration level when robot sensitivity was higher than human sensitivity. In general, collaboration of human and robot in target recognition tasks will improve upon the optimal performance of a single human detector.

关键词： Human-robot interaction levels of automation objective function target recognition unstructured environments

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Estimation of an optimal solution of a LP problem with unknown objective function - A stochastic approximation approach based on the simplex method

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MATHEMATICAL PROGRAMMING 2004年第3期101卷 463-478页

作者： Prieto-Rumeau, T Univ Nacl Educ Distancia Dept Econ Aplicada Cuantitat 2 Madrid Spain

We consider a linear programming problem with unknown objective function. Random observations related to the unknown objective function are sequentially available. We define a stochastic algorithm, based on the simplex method, that estimates an optimal solution of the linear programming problem. It is shown that this algorithm converges with probability one to the set of optimal solutions and that its failure probability is of order inversely proportional to the sample size. We also introduce stopping criteria for the algorithm. The asymptotic normality of some suitably defined residuals is also analyzed. The proposed estimation algorithm is motivated by the stochastic approximation algorithms but it introduces a generalization of these techniques when the linear programming problem has several optimal solutions. The proposed algorithm is also close to the stochastic quasi-gradient procedures, though their usual assumptions are weakened.

关键词： objective function Mathematical Method Approximation Algorithm Programming Problem Failure Probability

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Static and Dynamic Community Detection Methods That Optimize a Specific objective function: A Survey and Experimental Evaluation

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IEEE ACCESS 2020年 8卷 98330-98358页

作者： Taha, Kamal Khalifa Univ Dept Elect & Comp Sci Abu Dhabi U Arab Emirates

Most current survey papers classify community detection methods into broad categories and do not draw clear boundaries between the specific techniques employed by these methods. We survey in this paper all fine-grained community detection categories, the clustering methods that fall under these categories, and the techniques employed by these methods for optimizing each objective function. We provide methodology-based taxonomies that classify static and dynamic community detection methods into hierarchically nested, fine-grained, and specific classes. We classify the methods into the objective function they optimize. Each objective function class is classified into clustering categories. Each category is further classified into clustering methods. Methods are further classified into sub-methods and so on. Thus, the lowest subclass in a hierarchy is a fine-grained and specific method. For each method, we survey the different techniques in literature employed by the method. We empirically and experimentally compare and rank the different methods that fall under each clustering category. We also empirically and experimentally compare and rank the different categories that optimize a same objective function. In summary, the block-based, top-down divisive-based, random walk-based, and matrix eigenvector-based methods achieved good results. Finally, we provide fitness metrics for each objective function.

关键词： Linear programming Clustering methods Taxonomy Clustering algorithms Heuristic algorithms Measurement Classification algorithms Clustering community detection objective function

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Influences of feeding conditions and objective function on the optimal design of gas flow channel of a PEM fuel cell

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INTERNATIONAL JOURNAL OF HYDROGEN ENERGY 2017年第36期42卷 23141-23159页

作者： Mahmoudimehr, Javad Daryadel, Amirhosein Univ Guilan Dept Mech Engn Fac Engn POB 3756 Rasht Iran

Polymer electrolyte membrane fuel cell (PEMFC) is one of the promising electricity generating technologies with a wide range of applicability;however, it needs further improvements to be commercially viable. The design of a PEMFC plays a key role in its viability, and is often reduced to the design of gas flow channel (GFC) at the cathode side. In this study, it is attempted to figure out the optimal dimensions (i.e., width and height) of the rectangular cross sectional area of the cathode GFC of a PEMFC via numerical examination of various sets of dimensions. The optimization procedure is carried out for two different objective functions (the maximization of the maximum power and the maximization of the average power over a range of operating voltages) as well as for different sets of operating conditions (cell temperature, operating pressure, and stoichiometry and relative humidity of inlet gases). To the best of authors' knowledge, the following observations may be considered to be the contributions of the present work to the subject: First, the influence of cross sectional dimensions on the PEMFC performance is considerable, and this considerable influence is not limited to a specific set of operating conditions. Second, the performance of the PEMFC may both deteriorate and improve with the channel width or height, depending on its operating conditions as well as on its current dimensions. Third, there exists no single optimal cross section for different sets of operating conditions. Fourth, the polarization curves of two different cross sections may intersect, and as a result, one cross section may have a greater maximum power but at the same time lower average power in comparison to the other one. And fifth, among all the operating parameters, the relative humidity of inlet gases has the greatest effect on the optimal cross sectional dimensions. (C) 2017 Hydrogen Energy Publications LLC. Published by Elsevier Ltd. All rights reserved.

关键词： PEM fuel cell Channel design Optimization Feeding conditions objective function

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Closed-loop control dynamic obstacle avoidance algorithm based on a machine learning objective function

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JOURNAL OF MECHANICAL SCIENCE AND TECHNOLOGY 2024年第6期38卷 3089-3099页

作者： Rong, Yu Dou, Tianci Zhang, Xingchao Yanshan Univ Sch Vehicle & Energy Qinhuangdao 066004 Hebei Peoples R China

In this work, we address the issue of insufficient accuracy in the gradient projection algorithm and propose a closed-loop control dynamic obstacle avoidance algorithm that relies on a machine learning objective function. We initially establish a reasonable objective function and employ the gradient descent algorithm to enable dynamic obstacle avoidance in each bar. We then separate the end trajectory of the manipulator into multiple trajectory points and use the actual and expected positions of the end as the starting and ending points to significantly enhance the end tracking accuracy of the manipulator. Finally, we conduct simulation and real experiments on planar four degrees-of-freedom redundant manipulators to validate the efficacy of the algorithm. Moreover, the algorithm is proven to be applicable to dynamic obstacle avoidance under various trajectory tracking scenarios. It also exhibits advantages, such as smooth and continuous avoidance states and low computational costs.

关键词： Redundancy robot Null space characteristics objective function Dynamic obstacle avoidance

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