Selecting optimization ship form scheme is an important content in the process of concept design of ship. Multi-objective fuzzy decision-making model for ship form demonstration is set up according to the fuzzy patter...Selecting optimization ship form scheme is an important content in the process of concept design of ship. Multi-objective fuzzy decision-making model for ship form demonstration is set up according to the fuzzy pattern-recognition theory. Weight coefficients of each target of ship form scheme are determined by information entropy and individual subjective partiality. This model is used to select the optimal ship form scheme, the example shows that the model is exact and the resuh is credible. It can provide a reference for choosing the optimization scheme of ship form.展开更多
Modeling and optimizing long-term energy systems can provide solutions to various energy and environmental policies involving public-interest issues.The conventional optimization of long-term energy system models focu...Modeling and optimizing long-term energy systems can provide solutions to various energy and environmental policies involving public-interest issues.The conventional optimization of long-term energy system models focuses on a single economic goal.However,the increasingly complex demands of energy systems necessitate the comprehensive consideration of multiple dimensional objectives,such as environmental,social,and energy security.Therefore,a multi-objective optimization of long-term energy system models has been developed.Herein,studies pertaining to the multi-objective optimization of long-term energy system models are summarized;the optimization objectives of long-term energy system models are classified into economic,environmental,social,and energy security aspects;and the multi-objective optimization methods are classified and explained based on the preferential expression of decision makers.Finally,the key development direction of the multi-objective optimization of energy system models is discussed.展开更多
There exists large space to save energy of high-sulfur natural gas purification process.The multi-objective optimization problem has been investigated to effectively reduce the total comprehensive energy consumption a...There exists large space to save energy of high-sulfur natural gas purification process.The multi-objective optimization problem has been investigated to effectively reduce the total comprehensive energy consumption and further improve the production rate of purified gas.A steady-state simulation model of high-sulfur natural gas purification process has been set up by using ProMax.Seven key operating parameters of the purification process have been determined based on the analysis of comprehensive energy consumption distribution.To solve the problem that the process model does not converge in some conditions,back-propagation(BP)neural network has been applied to substitute the simulation model to predict the relative parameters in the optimization model.The uniform design method and the table U21(107)have been applied to design the experiment points for training and testing BP model.High prediction accuracy can be achieved by using the BP model.Nondominated sorting genetic algorithm-II has been developed to optimize the two objectives,and 100 Pareto optimal solutions have been obtained.Three optimal points have been selected and evaluated further.The results demonstrate that the total comprehensive energy consumption is reduced by 13.4%and the production rate of purified gas is improved by 0.2%under the optimized operating conditions.展开更多
The influence of processing parameters on the precision of parts fabricated by fused deposition modeling （FDM） technology is studied based on a series of performed experiments. Processing parameters of FDM in terms ...The influence of processing parameters on the precision of parts fabricated by fused deposition modeling （FDM） technology is studied based on a series of performed experiments. Processing parameters of FDM in terms of wire-width compensation, extrusion velocity, filing velocity, and layer thickness are chosen as the control fac- tors. Robust design analysis and multi-index fuzzy comprehensive assessment method are used to obtain the opti- mal parameters. Results show that the influencing degrees of these four factors on the precision of as-processed parts are different. The optimizations of individual parameters and their combined effects are of the same impor- tance for a high precision manufacturing.展开更多
This paper presents a method to design a control scheme for nonlinear systems using fuzzy optimal control.In the design process,the nonlinear system is first converted into local subsystems using sector non linearity ...This paper presents a method to design a control scheme for nonlinear systems using fuzzy optimal control.In the design process,the nonlinear system is first converted into local subsystems using sector non linearity approach of Takagi Sugeno(T S)fuzzy modeling.For each local subsystem,an optimal control is designed.Then,the parameters of local controllers are defuzzified to construct a global optimal controller.To prove the effectiveness of this control scheme,simulations are performed using the mathematical model of Esso Osaka tanker ship for set point regulation with and without disturbance and reference tracking.In addition,the simulation results are compared with that of a PID controller for further verification and validation.It has been shown that the proposed optimal controller can be used for the nonlinear ship steering with good rise time,zero steady state error and fast settling time.展开更多
Model updating for aircraft in a high temperature environment(HTE)is proposed based on the hierarchical method.With this method,the problem can be decomposed into temperature field updating and dynamic structural upda...Model updating for aircraft in a high temperature environment(HTE)is proposed based on the hierarchical method.With this method,the problem can be decomposed into temperature field updating and dynamic structural updating.In order to improve the estimation accuracy,the model updating problem is turned into a multi-objective optimization problem by constructing the objective function which combined with residues of modal frequency and effective modal mass.Then the metamodeling,support vector regression(SVR)is introduced to improve the optimization efficiency,and the solution can be determined by adaptive weighted-sum method(AWS).Finally,the proposed method is tested on a finite element(FE)model of a reentry vehicle model.The results show that the multi-objective model updating method in HTE can identify the input parameters of the temperature field and structure with good accuracy.展开更多
文摘Selecting optimization ship form scheme is an important content in the process of concept design of ship. Multi-objective fuzzy decision-making model for ship form demonstration is set up according to the fuzzy pattern-recognition theory. Weight coefficients of each target of ship form scheme are determined by information entropy and individual subjective partiality. This model is used to select the optimal ship form scheme, the example shows that the model is exact and the resuh is credible. It can provide a reference for choosing the optimization scheme of ship form.
基金This research was financially supported by the National Natural Science Foundation of China(No.72371102).
文摘Modeling and optimizing long-term energy systems can provide solutions to various energy and environmental policies involving public-interest issues.The conventional optimization of long-term energy system models focuses on a single economic goal.However,the increasingly complex demands of energy systems necessitate the comprehensive consideration of multiple dimensional objectives,such as environmental,social,and energy security.Therefore,a multi-objective optimization of long-term energy system models has been developed.Herein,studies pertaining to the multi-objective optimization of long-term energy system models are summarized;the optimization objectives of long-term energy system models are classified into economic,environmental,social,and energy security aspects;and the multi-objective optimization methods are classified and explained based on the preferential expression of decision makers.Finally,the key development direction of the multi-objective optimization of energy system models is discussed.
基金Financial support from National Science and Technology Major Project of the Ministry of Science and Technology of China(Grant No.2016ZX05017-004)
文摘There exists large space to save energy of high-sulfur natural gas purification process.The multi-objective optimization problem has been investigated to effectively reduce the total comprehensive energy consumption and further improve the production rate of purified gas.A steady-state simulation model of high-sulfur natural gas purification process has been set up by using ProMax.Seven key operating parameters of the purification process have been determined based on the analysis of comprehensive energy consumption distribution.To solve the problem that the process model does not converge in some conditions,back-propagation(BP)neural network has been applied to substitute the simulation model to predict the relative parameters in the optimization model.The uniform design method and the table U21(107)have been applied to design the experiment points for training and testing BP model.High prediction accuracy can be achieved by using the BP model.Nondominated sorting genetic algorithm-II has been developed to optimize the two objectives,and 100 Pareto optimal solutions have been obtained.Three optimal points have been selected and evaluated further.The results demonstrate that the total comprehensive energy consumption is reduced by 13.4%and the production rate of purified gas is improved by 0.2%under the optimized operating conditions.
基金Supported by the Science and Technology Support Key Project of 12th Five-Year of China(2011BAD20B00-4)~~
文摘The influence of processing parameters on the precision of parts fabricated by fused deposition modeling （FDM） technology is studied based on a series of performed experiments. Processing parameters of FDM in terms of wire-width compensation, extrusion velocity, filing velocity, and layer thickness are chosen as the control fac- tors. Robust design analysis and multi-index fuzzy comprehensive assessment method are used to obtain the opti- mal parameters. Results show that the influencing degrees of these four factors on the precision of as-processed parts are different. The optimizations of individual parameters and their combined effects are of the same impor- tance for a high precision manufacturing.
基金supported in part by the National Natural Science Foundation of China (No. 61751210)the Jiangsu Natural Science Foundation of China (No. BK20171417)the Fundamental Research Funds for the Central Universities(No. NG2019002)
文摘This paper presents a method to design a control scheme for nonlinear systems using fuzzy optimal control.In the design process,the nonlinear system is first converted into local subsystems using sector non linearity approach of Takagi Sugeno(T S)fuzzy modeling.For each local subsystem,an optimal control is designed.Then,the parameters of local controllers are defuzzified to construct a global optimal controller.To prove the effectiveness of this control scheme,simulations are performed using the mathematical model of Esso Osaka tanker ship for set point regulation with and without disturbance and reference tracking.In addition,the simulation results are compared with that of a PID controller for further verification and validation.It has been shown that the proposed optimal controller can be used for the nonlinear ship steering with good rise time,zero steady state error and fast settling time.
基金supported by the National Natural Science Foundation of China(No.11472132)the Fundamental Research Funds for Central University (No. NJ20160050)the Fundamental Research Funds for Central University(No.NJ2016098)
文摘Model updating for aircraft in a high temperature environment(HTE)is proposed based on the hierarchical method.With this method,the problem can be decomposed into temperature field updating and dynamic structural updating.In order to improve the estimation accuracy,the model updating problem is turned into a multi-objective optimization problem by constructing the objective function which combined with residues of modal frequency and effective modal mass.Then the metamodeling,support vector regression(SVR)is introduced to improve the optimization efficiency,and the solution can be determined by adaptive weighted-sum method(AWS).Finally,the proposed method is tested on a finite element(FE)model of a reentry vehicle model.The results show that the multi-objective model updating method in HTE can identify the input parameters of the temperature field and structure with good accuracy.
