The conventional data envelopment analysis （DEA） measures the relative efficiencies of a set of decision making units with exact values of inputs and outputs. In real-world prob- lems, however, inputs and outputs ty...The conventional data envelopment analysis （DEA） measures the relative efficiencies of a set of decision making units with exact values of inputs and outputs. In real-world prob- lems, however, inputs and outputs typically have some levels of fuzziness. To analyze a decision making unit （DMU） with fuzzy input/output data, previous studies provided the fuzzy DEA model and proposed an associated evaluating approach. Nonetheless, numerous deficiencies must still be improved, including the α- cut approaches, types of fuzzy numbers, and ranking techniques. Moreover, a fuzzy sample DMU still cannot be evaluated for the Fuzzy DEA model. Therefore, this paper proposes a fuzzy DEA model based on sample decision making unit （FSDEA）. Five eval- uation approaches and the related algorithm and ranking methods are provided to test the fuzzy sample DMU of the FSDEA model. A numerical experiment is used to demonstrate and compare the results with those obtained using alternative approaches.展开更多
Microbial fuel cell(MFC)is a kind of promising clean power supply energy equipment,but serious nonlinearities and disturbances exist when the MFC runs,and it is an important topic to guarantee that the output voltage ...Microbial fuel cell(MFC)is a kind of promising clean power supply energy equipment,but serious nonlinearities and disturbances exist when the MFC runs,and it is an important topic to guarantee that the output voltage reaches the setting value quickly and smoothly.Regulating the feeding flow is an effective way to achieve this goal,and especially,the satisfactory results can be achieved by regulating anode feeding flow.In this work,a feedforward fuzzy logic PID algorithm is proposed.The fuzzy logic system is introduced to deal with the non-linear dynamics of MFC,and corresponding PID parameters are calculated according to defuzzification.The magnitude value of the current density is used to simulate the value of the external load.The simulation results indicate that the MFC output voltage can track the setting value quickly and smoothly with the proposed feedforward fuzzy logic PID algorithm.The proposed algorithm is more efficient and robust with respect to anti-disturbance performance and tracking accuracy than other three control methods.展开更多
For the system with the fuzzy failure state, the effects of the input random variables and the fuzzy failure state on the fuzzy probability of failure for the structural system are studied, and the moment-independence...For the system with the fuzzy failure state, the effects of the input random variables and the fuzzy failure state on the fuzzy probability of failure for the structural system are studied, and the moment-independence global sensitivity analysis（GSA） model is proposed to quantitatively measure these effects. According to the fuzzy random theory, the fuzzy failure state is transformed into an equivalent new random variable for the system, and the complementary function of the membership function of the fuzzy failure state is defined as the cumulative distribution function（CDF） of the new random variable. After introducing the new random variable, the equivalent performance function of the original problem is built. The difference between the unconditional fuzzy probability of failure and conditional fuzzy probability of failure is defined as the moment-independent GSA index. In order to solve the proposed GSA index efficiently, the Kriging-based algorithm is developed to estimate the defined moment-independence GSA index. Two engineering examples are employed to verify the feasibility and rationality of the presented GSA model, and the advantages of the developed Kriging method are also illustrated.展开更多
Randomness and fuzziness are among the attributes of the influential factors for stability assessment of pile foundation. According to these two characteristics, the triangular fuzzy number analysis approach was intro...Randomness and fuzziness are among the attributes of the influential factors for stability assessment of pile foundation. According to these two characteristics, the triangular fuzzy number analysis approach was introduced to determine the probability-distributed function of mechanical parameters. Then the functional function of reliability analysis was constructed based on the study of bearing mechanism of pile foundation, and the way to calculate interval values of the functional function was developed by using improved interval-truncation approach and operation rules of interval numbers. Afterwards, the non-probabilistic fuzzy reliability analysis method was applied to assessing the pile foundation, from which a method was presented for non- probabilistic fuzzy reliability analysis of pile foundation stability by interval theory. Finally, the probability distribution curve of non- probabilistic fuzzy reliability indexes of practical pile foundation was concluded. Its failure possibility is 0.91%, which shows that the pile foundation is stable and reliable.展开更多
The analytical structures and the corresponding mathematical properties of the one dimensional and two dimensional fuzzy controllers are first investigated in detail. The nature of these two kinds of fuzzy controllers...The analytical structures and the corresponding mathematical properties of the one dimensional and two dimensional fuzzy controllers are first investigated in detail. The nature of these two kinds of fuzzy controllers is next probed from the perspective of control engineering. For the one dimensional fuzzy controller, it is concluded that this controller is a combination of a saturation element and a nonlinear proportional controller, and the system that employs the one dimensional fuzzy controller is the combination of an open-loop control system and a closedloop control system. For the latter case, it is concluded that it is a hybrid controller, which comprises the saturation part, zero-output part, nonlinear derivative part, nonlinear proportional part, as well as nonlinear proportional-derivative part, and the two dimensional fuzzy controller-based control system is a loop-varying system with varying number of control loops.展开更多
A frequency-domain-based sufficient condition is derived to guarantee the globally asymptotic stability of the simplest Takagi-Sugeno （T-S） fuzzy control system by using the circle criterion. The analysis is perform...A frequency-domain-based sufficient condition is derived to guarantee the globally asymptotic stability of the simplest Takagi-Sugeno （T-S） fuzzy control system by using the circle criterion. The analysis is performed in the frequency domain, and hence the condition is of great significance when the frequency-response method, which is widely used in the linear control theory and practice, is employed to synthesize the simplest T-S fuzzy controller. Besides, this sufficient condition is featured by a graphical interpretation, which makes the condition straightforward to be used. Comparisons are drawn between the performance of the simplest T-S fuzzy controller and that of the linear compensator. Two numerical examples are presented to demonstrate how this sufficient condition can be applied to both stable and unstable plants.展开更多
Cables that have been in service for over 20 years in Shanghai, a city with abundant surface water, failed more frequently and induced different cable accidents. This necessitates researches on the insulation aging st...Cables that have been in service for over 20 years in Shanghai, a city with abundant surface water, failed more frequently and induced different cable accidents. This necessitates researches on the insulation aging state of cables working in special circumstances. We performed multi-parameter tests with samples from about 300 cable lines in Shanghai. The tests included water tree investigation, tensile test, dielectric spectroscopy test, thermogravimetric analysis (TGA), fourier transform infrared spectroscopy (FTIR), and electrical aging test. Then, we carried out regression analysis between every two test parameters. Moreover, through two-sample t-Test and analysis of va- riance (ANOVA) of each test parameter, we analyzed the influences of cable-laying method and sampling section on the degradation of cable insulation respectively. Furthermore, the test parameters which have strong correlation in the regression analysis or significant differ- ences in the t-Test or ANOVA analysis were determined to be the ones identifying the XLPE cable insulation aging state. The thresholds for distinguishing insulation aging states had been also obtained with the aid of statistical analysis and fuzzy clustering. Based on the fuzzy in- ference, we established a cable insulation aging diagnosis model using the intensity transfer method. The results of regression analysis indicate that the degradation of cable insulation accelerates as the degree of in-service aging increases. This validates the rule that the in- crease of microscopic imperfections in solid material enhances the dielectric breakdown strength. The results of the two-sample t-Test and the ANOVA indicate that the direct-buried cables are more sensitive to insulation degradation than duct cables. This confirms that the tensile strength and breakdown strength are reliable functional parameters in cable insulation evaluations. A case study further indicates that the proposed diagnosis model based on the fuzzy inference can reflect the comprehensive aging state of cable insulation well, and that the cable service time has no correlation with the insulation aging state.展开更多
The thermal-induced error is a very important sour ce of machining errors of machine tools. To compensate the thermal-induced machin ing errors, a relationship model between the thermal field and deformations was need...The thermal-induced error is a very important sour ce of machining errors of machine tools. To compensate the thermal-induced machin ing errors, a relationship model between the thermal field and deformations was needed. The relationship can be deduced by virtual of FEM (Finite Element Method ), ANN (Artificial Neural Network) or MRA (Multiple Regression Analysis). MR A is on the basis of a total understanding of the temperature distribution of th e machine tool. Although the more the temperatures measured are, the more accura te the MRA is, too more temperatures will hinder the analysis calculation. So it is necessary to identify the key temperatures of the machine tool. The selectio n of key temperatures decides the efficiency and precision of MRA. Because of th e complexities and multi-input and multi-output structure of the relationships , the exact quantitative portions as well as the unclear portions must be taken into consideration together to improve the identification of key temperatures. I n this paper, a fuzzy cluster analysis was used to select the key temperatures. The substance of identifying the key temperatures is to group all temperatures b y their relativity, and then to select a temperature from each group as the repr esentation. A fuzzy cluster analysis can uncover the relationships between t he thermal field and deformations more truly and thoroughly. A fuzzy cluster ana lysis is the cluster analysis based on fuzzy sets. Given U={u i|i=0,...,N}, in which u i is the temperature measured, a fuzzy matrix R can be obta ined. The transfer close package t(R) can be deduced from R. A fuzzy clu ster of U then conducts on the basis of t(R). Based on the fuzzy cluster analysis discussed above, this paper identified the k ey temperatures of a horizontal machining center. The number of the temperatures measured was reduced to 4 from 32, and then the multiple regression relationshi p models between the 4 temperatures and the thermal deformations of the spindle were drawn. The remnant errors between the regression models and measured deform ations reached a satisfying low level. At the same time, the decreasing of tempe rature variable number improved the efficiency of measure and analysis greatly.展开更多
为探究有限区间条件下的随机场空间变异性特征及其对边坡稳定性的影响机制,提出了考虑岩土体参数模糊不确定性的边坡地震稳定性概率分析方法。首先,基于熵的统一测度框架,推导有限区间下模糊熵和概率熵计算式;然后,利用熵等价法将模糊...为探究有限区间条件下的随机场空间变异性特征及其对边坡稳定性的影响机制,提出了考虑岩土体参数模糊不确定性的边坡地震稳定性概率分析方法。首先,基于熵的统一测度框架,推导有限区间下模糊熵和概率熵计算式;然后,利用熵等价法将模糊变量转换为等效随机变量,结合随机场理论和有限差分法,建立考虑岩土体参数区间影响和模糊不确定性的随机有限差分模型;最后采用拟静力分析法,开展有限区间及随机场参数影响下的边坡地震稳定性概率分析。研究结果表明:假设变量属于无穷区间会高估熵值且低估等效变异系数(coefficient of variation,COV),得到的边坡稳定性概率分析结果偏向非保守。随着有限区间的扩大,熵值曲线呈上凸型持续增加,边坡失效概率从7.04×10^(−3)减小至1.39×10^(−4),但安全系数(factor of safety,FOS)均值始终小于均质模型FOS=1.66。随机场空间变异性特征越明显,蒙特卡洛模拟(Monte Carlo simulation,MCS)统计结果的COV越大,边坡失效概率越高,边坡稳定性对随机场参数的敏感性顺序为:COV>互相关系数>相关长度。边坡在第三水准地震荷载作用下失效概率达到42.07%,但FOS均值仍大于1.15,说明概率分析方法比确定性分析方法能够提供更多的边坡稳定状态信息,而确定性分析方法得出的边坡稳定评估结果偏于冒险。研究成果可为考虑岩土体参数实际区间及模糊不确定性的边坡地震稳定性概率分析提供参考。展开更多
基金supported by the National Natural Science Foundation of China (70961005)211 Project for Postgraduate Student Program of Inner Mongolia University+1 种基金National Natural Science Foundation of Inner Mongolia (2010Zd342011MS1002)
文摘The conventional data envelopment analysis （DEA） measures the relative efficiencies of a set of decision making units with exact values of inputs and outputs. In real-world prob- lems, however, inputs and outputs typically have some levels of fuzziness. To analyze a decision making unit （DMU） with fuzzy input/output data, previous studies provided the fuzzy DEA model and proposed an associated evaluating approach. Nonetheless, numerous deficiencies must still be improved, including the α- cut approaches, types of fuzzy numbers, and ranking techniques. Moreover, a fuzzy sample DMU still cannot be evaluated for the Fuzzy DEA model. Therefore, this paper proposes a fuzzy DEA model based on sample decision making unit （FSDEA）. Five eval- uation approaches and the related algorithm and ranking methods are provided to test the fuzzy sample DMU of the FSDEA model. A numerical experiment is used to demonstrate and compare the results with those obtained using alternative approaches.
基金Project(61563032)supported by the National Natural Science Foundation of ChinaProject(18JR3RA133)supported by Gansu Basic Research Innovation Group,China
文摘Microbial fuel cell(MFC)is a kind of promising clean power supply energy equipment,but serious nonlinearities and disturbances exist when the MFC runs,and it is an important topic to guarantee that the output voltage reaches the setting value quickly and smoothly.Regulating the feeding flow is an effective way to achieve this goal,and especially,the satisfactory results can be achieved by regulating anode feeding flow.In this work,a feedforward fuzzy logic PID algorithm is proposed.The fuzzy logic system is introduced to deal with the non-linear dynamics of MFC,and corresponding PID parameters are calculated according to defuzzification.The magnitude value of the current density is used to simulate the value of the external load.The simulation results indicate that the MFC output voltage can track the setting value quickly and smoothly with the proposed feedforward fuzzy logic PID algorithm.The proposed algorithm is more efficient and robust with respect to anti-disturbance performance and tracking accuracy than other three control methods.
基金supported by the National Natural Science Foundation of China(11702281)the Science Challenge Project(TZ2018007)the Technology Foundation Project of State Administration of Science,Technology and Industry for National Defence,PRC(JSZL2017212A001)
文摘For the system with the fuzzy failure state, the effects of the input random variables and the fuzzy failure state on the fuzzy probability of failure for the structural system are studied, and the moment-independence global sensitivity analysis（GSA） model is proposed to quantitatively measure these effects. According to the fuzzy random theory, the fuzzy failure state is transformed into an equivalent new random variable for the system, and the complementary function of the membership function of the fuzzy failure state is defined as the cumulative distribution function（CDF） of the new random variable. After introducing the new random variable, the equivalent performance function of the original problem is built. The difference between the unconditional fuzzy probability of failure and conditional fuzzy probability of failure is defined as the moment-independent GSA index. In order to solve the proposed GSA index efficiently, the Kriging-based algorithm is developed to estimate the defined moment-independence GSA index. Two engineering examples are employed to verify the feasibility and rationality of the presented GSA model, and the advantages of the developed Kriging method are also illustrated.
基金Project(50378036) supported by the National Natural Science Foundation of ChinaProject(03JJY5024) supported by the Natural Science Foundation of Hunan Province, China
文摘Randomness and fuzziness are among the attributes of the influential factors for stability assessment of pile foundation. According to these two characteristics, the triangular fuzzy number analysis approach was introduced to determine the probability-distributed function of mechanical parameters. Then the functional function of reliability analysis was constructed based on the study of bearing mechanism of pile foundation, and the way to calculate interval values of the functional function was developed by using improved interval-truncation approach and operation rules of interval numbers. Afterwards, the non-probabilistic fuzzy reliability analysis method was applied to assessing the pile foundation, from which a method was presented for non- probabilistic fuzzy reliability analysis of pile foundation stability by interval theory. Finally, the probability distribution curve of non- probabilistic fuzzy reliability indexes of practical pile foundation was concluded. Its failure possibility is 0.91%, which shows that the pile foundation is stable and reliable.
基金This project was supported by the fundation of the Academy of Finland (201353)
文摘The analytical structures and the corresponding mathematical properties of the one dimensional and two dimensional fuzzy controllers are first investigated in detail. The nature of these two kinds of fuzzy controllers is next probed from the perspective of control engineering. For the one dimensional fuzzy controller, it is concluded that this controller is a combination of a saturation element and a nonlinear proportional controller, and the system that employs the one dimensional fuzzy controller is the combination of an open-loop control system and a closedloop control system. For the latter case, it is concluded that it is a hybrid controller, which comprises the saturation part, zero-output part, nonlinear derivative part, nonlinear proportional part, as well as nonlinear proportional-derivative part, and the two dimensional fuzzy controller-based control system is a loop-varying system with varying number of control loops.
文摘A frequency-domain-based sufficient condition is derived to guarantee the globally asymptotic stability of the simplest Takagi-Sugeno （T-S） fuzzy control system by using the circle criterion. The analysis is performed in the frequency domain, and hence the condition is of great significance when the frequency-response method, which is widely used in the linear control theory and practice, is employed to synthesize the simplest T-S fuzzy controller. Besides, this sufficient condition is featured by a graphical interpretation, which makes the condition straightforward to be used. Comparisons are drawn between the performance of the simplest T-S fuzzy controller and that of the linear compensator. Two numerical examples are presented to demonstrate how this sufficient condition can be applied to both stable and unstable plants.
基金Project supported by National Natural Science Foundation of China（51277117）, Shang- hai Science and Technology Comrmssion（11 DZ2283000）.
文摘Cables that have been in service for over 20 years in Shanghai, a city with abundant surface water, failed more frequently and induced different cable accidents. This necessitates researches on the insulation aging state of cables working in special circumstances. We performed multi-parameter tests with samples from about 300 cable lines in Shanghai. The tests included water tree investigation, tensile test, dielectric spectroscopy test, thermogravimetric analysis (TGA), fourier transform infrared spectroscopy (FTIR), and electrical aging test. Then, we carried out regression analysis between every two test parameters. Moreover, through two-sample t-Test and analysis of va- riance (ANOVA) of each test parameter, we analyzed the influences of cable-laying method and sampling section on the degradation of cable insulation respectively. Furthermore, the test parameters which have strong correlation in the regression analysis or significant differ- ences in the t-Test or ANOVA analysis were determined to be the ones identifying the XLPE cable insulation aging state. The thresholds for distinguishing insulation aging states had been also obtained with the aid of statistical analysis and fuzzy clustering. Based on the fuzzy in- ference, we established a cable insulation aging diagnosis model using the intensity transfer method. The results of regression analysis indicate that the degradation of cable insulation accelerates as the degree of in-service aging increases. This validates the rule that the in- crease of microscopic imperfections in solid material enhances the dielectric breakdown strength. The results of the two-sample t-Test and the ANOVA indicate that the direct-buried cables are more sensitive to insulation degradation than duct cables. This confirms that the tensile strength and breakdown strength are reliable functional parameters in cable insulation evaluations. A case study further indicates that the proposed diagnosis model based on the fuzzy inference can reflect the comprehensive aging state of cable insulation well, and that the cable service time has no correlation with the insulation aging state.
文摘The thermal-induced error is a very important sour ce of machining errors of machine tools. To compensate the thermal-induced machin ing errors, a relationship model between the thermal field and deformations was needed. The relationship can be deduced by virtual of FEM (Finite Element Method ), ANN (Artificial Neural Network) or MRA (Multiple Regression Analysis). MR A is on the basis of a total understanding of the temperature distribution of th e machine tool. Although the more the temperatures measured are, the more accura te the MRA is, too more temperatures will hinder the analysis calculation. So it is necessary to identify the key temperatures of the machine tool. The selectio n of key temperatures decides the efficiency and precision of MRA. Because of th e complexities and multi-input and multi-output structure of the relationships , the exact quantitative portions as well as the unclear portions must be taken into consideration together to improve the identification of key temperatures. I n this paper, a fuzzy cluster analysis was used to select the key temperatures. The substance of identifying the key temperatures is to group all temperatures b y their relativity, and then to select a temperature from each group as the repr esentation. A fuzzy cluster analysis can uncover the relationships between t he thermal field and deformations more truly and thoroughly. A fuzzy cluster ana lysis is the cluster analysis based on fuzzy sets. Given U={u i|i=0,...,N}, in which u i is the temperature measured, a fuzzy matrix R can be obta ined. The transfer close package t(R) can be deduced from R. A fuzzy clu ster of U then conducts on the basis of t(R). Based on the fuzzy cluster analysis discussed above, this paper identified the k ey temperatures of a horizontal machining center. The number of the temperatures measured was reduced to 4 from 32, and then the multiple regression relationshi p models between the 4 temperatures and the thermal deformations of the spindle were drawn. The remnant errors between the regression models and measured deform ations reached a satisfying low level. At the same time, the decreasing of tempe rature variable number improved the efficiency of measure and analysis greatly.
文摘为探究有限区间条件下的随机场空间变异性特征及其对边坡稳定性的影响机制,提出了考虑岩土体参数模糊不确定性的边坡地震稳定性概率分析方法。首先,基于熵的统一测度框架,推导有限区间下模糊熵和概率熵计算式;然后,利用熵等价法将模糊变量转换为等效随机变量,结合随机场理论和有限差分法,建立考虑岩土体参数区间影响和模糊不确定性的随机有限差分模型;最后采用拟静力分析法,开展有限区间及随机场参数影响下的边坡地震稳定性概率分析。研究结果表明:假设变量属于无穷区间会高估熵值且低估等效变异系数(coefficient of variation,COV),得到的边坡稳定性概率分析结果偏向非保守。随着有限区间的扩大,熵值曲线呈上凸型持续增加,边坡失效概率从7.04×10^(−3)减小至1.39×10^(−4),但安全系数(factor of safety,FOS)均值始终小于均质模型FOS=1.66。随机场空间变异性特征越明显,蒙特卡洛模拟(Monte Carlo simulation,MCS)统计结果的COV越大,边坡失效概率越高,边坡稳定性对随机场参数的敏感性顺序为:COV>互相关系数>相关长度。边坡在第三水准地震荷载作用下失效概率达到42.07%,但FOS均值仍大于1.15,说明概率分析方法比确定性分析方法能够提供更多的边坡稳定状态信息,而确定性分析方法得出的边坡稳定评估结果偏于冒险。研究成果可为考虑岩土体参数实际区间及模糊不确定性的边坡地震稳定性概率分析提供参考。
