The rapid evolution of unmanned aerial vehicle(UAV)technology and autonomous capabilities has positioned UAV as promising last-mile delivery means.Vehicle and onboard UAV collaborative delivery is introduced as a nove...The rapid evolution of unmanned aerial vehicle(UAV)technology and autonomous capabilities has positioned UAV as promising last-mile delivery means.Vehicle and onboard UAV collaborative delivery is introduced as a novel delivery mode.Spatiotemporal collaboration,along with energy consumption with payload and wind conditions play important roles in delivery route planning.This paper introduces the traveling salesman problem with time window and onboard UAV(TSPTWOUAV)and emphasizes the consideration of real-world scenarios,focusing on time collaboration and energy consumption with wind and payload.To address this,a mixed integer linear programming(MILP)model is formulated to minimize the energy consumption costs of vehicle and UAV.Furthermore,an adaptive large neighborhood search(ALNS)algorithm is applied to identify high-quality solutions efficiently.The effectiveness of the proposed model and algorithm is validated through numerical tests on real geographic instances and sensitivity analysis of key parameters is conducted.展开更多
In the hierarchical random effect linear model, the Bayes estimator of random parameter are not only dependent on specific prior distribution but also it is difficult to calculate in most cases. This paper derives the...In the hierarchical random effect linear model, the Bayes estimator of random parameter are not only dependent on specific prior distribution but also it is difficult to calculate in most cases. This paper derives the distributed-free optimal linear estimator of random parameters in the model by means of the credibility theory method. The estimators the authors derive can be applied in more extensive practical scenarios since they are only dependent on the first two moments of prior parameter rather than on specific prior distribution. Finally, the results are compared with some classical models and a numerical example is given to show the effectiveness of the estimators.展开更多
This paper focuses on synthesizing a mixed robust H_2/H_∞ linear parameter varying（LPV） controller for the longitudinal motion of an air-breathing hypersonic vehicle via a high order singular value decomposition（H...This paper focuses on synthesizing a mixed robust H_2/H_∞ linear parameter varying（LPV） controller for the longitudinal motion of an air-breathing hypersonic vehicle via a high order singular value decomposition（HOSVD） approach.The design of hypersonic flight control systems is highly challenging due to the enormous complexity of the vehicle dynamics and the presence of significant uncertainties.Motivated by recent results on both LPV control and tensor-product（TP） model transformation approach,the velocity and altitude tracking control problems for the air-breathing hypersonic vehicle is reduced to that of a state feedback stabilizing controller design for a polytopic LPV system with guaranteed performances.The controller implementation is converted into a convex optimization problem with parameterdependent linear matrix inequalities（LMIs） constraints,which is intuitively tractable using LMI control toolbox.Finally,numerical simulation results demonstrate the effectiveness of the proposed approach.展开更多
The class of bi-directional optimal velocity models can describe the bi-directional looking effect that usually exists in the reality and is even enhanced with the development of the connected vehicle technologies. It...The class of bi-directional optimal velocity models can describe the bi-directional looking effect that usually exists in the reality and is even enhanced with the development of the connected vehicle technologies. Its combined string stability condition can be obtained through the method of the ring-road based string stability analysis. However, the partial string stability about traffic fluctuation propagated backward or forward was neglected, which will be analyzed in detail in this work by the method of transfer function and its H∞ norm from the viewpoint of control theory. Then, through comparing the conditions of combined and partial string stabilities, their relationships can make traffic flow be divided into three distinguishable regions, displaying various combined and partial string stability performance. Finally, the numerical experiments verify the theoretical results and find that the final displaying string stability or instability performance results from the accumulated and offset effects of traffic fluctuations propagated from different directions.展开更多
Vehicle positioning with the global navigation satellite system （GNSS） in urban environments faces two problems which are attenuation and dynamic. For traditional GNSS receivers hardly able to track dynamic weak sig...Vehicle positioning with the global navigation satellite system （GNSS） in urban environments faces two problems which are attenuation and dynamic. For traditional GNSS receivers hardly able to track dynamic weak signals, the coupling between all visible satellite signals is ignored in the absence of navigation state feedback, and thermal noise error and dynamic stress threshold are contradictory due to non-coherent discriminators. The vector delay/frequency locked loop （VDFLL） with navigation state feedback and the joint vector tracking loop （JVTL） with coherent discriminator which is a synchronization parameter tracking loop based on maximum likelihood estimation （MLE） are proposed to improve the tracking sensitivity of GNSS receiver in dynamic weak signal environments. A joint vector position tracking loop （JVPTL） directly tracking user position and velocity is proposed to further improve tracking sensitivity. The coherent navigation parameter discriminator of JVPTL, being able to ease the contradiction between thermal noise error and dynamic stress threshold, is based on MLE according to the navigation parameter based linear model of received baseband signals. Simulation results show that JVPTL, which combines the advantages of both VDFLL and JVTL, performs better than both VDFLL and JVTL in dynamic weak signal environments.展开更多
A knowledge-based network for Section Yidong Bridge,Dongyang River,one tributary of Qiantang River,Zhejiang Province,China,is established in order to model water quality in areas under small data.Then,based on normal ...A knowledge-based network for Section Yidong Bridge,Dongyang River,one tributary of Qiantang River,Zhejiang Province,China,is established in order to model water quality in areas under small data.Then,based on normal transformation of variables with routine monitoring data and normal assumption of variables without routine monitoring data,a conditional linear Gaussian Bayesian network is constructed.A "two-constraint selection" procedure is proposed to estimate potential parameter values under small data.Among all potential parameter values,the ones that are most probable are selected as the "representatives".Finally,the risks of pollutant concentration exceeding national water quality standards are calculated and pollution reduction decisions for decision-making reference are proposed.The final results show that conditional linear Gaussian Bayesian network and "two-constraint selection" procedure are very useful in evaluating risks when there is limited data and can help managers to make sound decisions under small data.展开更多
The adaptive neuro-fuzzy inference systems(ANFIS)are widely used in the concrete technology.In this research,the compressive strength of light weight concrete was determined.To this end,the scoria percentage and curin...The adaptive neuro-fuzzy inference systems(ANFIS)are widely used in the concrete technology.In this research,the compressive strength of light weight concrete was determined.To this end,the scoria percentage and curing day variables were used as the input parameters,and compressive strength and tensile strength were used as the output parameters.In addition,100 patterns were used,70%of which were used for training and 30%were used for testing.To assess the precision of the neuro-fuzzy system,it was compared using two linear regression models.The comparisons were carried out in the training and testing phases.Research results revealed that the neuro-fuzzy systems model offers more potential,flexibility,and precision than the statistical models.展开更多
Many products always operate under various complex environment conditions. To describe the dynamic influence of environment factors on their reliability, a method of reliability sensitivity analysis is proposed. In th...Many products always operate under various complex environment conditions. To describe the dynamic influence of environment factors on their reliability, a method of reliability sensitivity analysis is proposed. In this method, the location parameter is assumed as a function of relevant environment variables while the scale parameter is assumed as an unknown positive constant. Then, the location parameter function is constructed by using the method of radial basis function. Using the varied environment test data, the log-likelihood function is transformed to a generalized linear expression by describing the indicator as Poisson variable. With the generalized linear model, the maximum likelihood estimations of the model coefficients are obtained. With the reliability model, the reliability sensitivity is obtained. An instance analysis shows that the method is feasible to analyze the dynamic variety characters of reliability along with environment factors and is straightforward for engineering application.展开更多
This paper proposes a robust method of parameter estimation and data classification for multiple-structural data based on the linear error in variable（EIV） model.The traditional EIV model fitting problem is analyzed...This paper proposes a robust method of parameter estimation and data classification for multiple-structural data based on the linear error in variable（EIV） model.The traditional EIV model fitting problem is analyzed and a robust growing algorithm is developed to extract the underlying linear structure of the observed data.Under the structural density assumption,the C-step technique borrowed from the Rousseeuw＇s robust MCD estimator is used to keep the algorithm robust and the mean-shift algorithm is adopted to ensure a good initialization.To eliminate the model ambiguities of the multiple-structural data,statistical hypotheses tests are used to refine the data classification and improve the accuracy of the model parameter estimation.Experiments show that the efficiency and robustness of the proposed algorithm.展开更多
基金Fundamental Research Funds for the Central Universities(2024JBZX038)National Natural Science F oundation of China(62076023)。
文摘The rapid evolution of unmanned aerial vehicle(UAV)technology and autonomous capabilities has positioned UAV as promising last-mile delivery means.Vehicle and onboard UAV collaborative delivery is introduced as a novel delivery mode.Spatiotemporal collaboration,along with energy consumption with payload and wind conditions play important roles in delivery route planning.This paper introduces the traveling salesman problem with time window and onboard UAV(TSPTWOUAV)and emphasizes the consideration of real-world scenarios,focusing on time collaboration and energy consumption with wind and payload.To address this,a mixed integer linear programming(MILP)model is formulated to minimize the energy consumption costs of vehicle and UAV.Furthermore,an adaptive large neighborhood search(ALNS)algorithm is applied to identify high-quality solutions efficiently.The effectiveness of the proposed model and algorithm is validated through numerical tests on real geographic instances and sensitivity analysis of key parameters is conducted.
基金supported by the National Science Foundation of China under Grant Nos.71361015,71340010,71371074the Jiangxi Provincial Natural Science Foundation under Grant No.20142BAB201013+2 种基金China Postdoctoral Science Foundation under Grant No.2013M540534China Postdoctoral Fund special Project under Grant No.2014T70615Jiangxi Postdoctoral Science Foundation under Grant No.2013KY53
文摘In the hierarchical random effect linear model, the Bayes estimator of random parameter are not only dependent on specific prior distribution but also it is difficult to calculate in most cases. This paper derives the distributed-free optimal linear estimator of random parameters in the model by means of the credibility theory method. The estimators the authors derive can be applied in more extensive practical scenarios since they are only dependent on the first two moments of prior parameter rather than on specific prior distribution. Finally, the results are compared with some classical models and a numerical example is given to show the effectiveness of the estimators.
基金supported by the National Natural Science Foundation of China(6120300761304239+1 种基金61503392)the Natural Science Foundation of Shaanxi Province(2015JQ6213)
文摘This paper focuses on synthesizing a mixed robust H_2/H_∞ linear parameter varying（LPV） controller for the longitudinal motion of an air-breathing hypersonic vehicle via a high order singular value decomposition（HOSVD） approach.The design of hypersonic flight control systems is highly challenging due to the enormous complexity of the vehicle dynamics and the presence of significant uncertainties.Motivated by recent results on both LPV control and tensor-product（TP） model transformation approach,the velocity and altitude tracking control problems for the air-breathing hypersonic vehicle is reduced to that of a state feedback stabilizing controller design for a polytopic LPV system with guaranteed performances.The controller implementation is converted into a convex optimization problem with parameterdependent linear matrix inequalities（LMIs） constraints,which is intuitively tractable using LMI control toolbox.Finally,numerical simulation results demonstrate the effectiveness of the proposed approach.
基金Projects(51108465,71371192)supported by the National Natural Science Foundation of ChinaProject(2014M552165)supported by China Postdoctoral Science FoundationProject(20113187851460)supported by Technology Project of the Ministry of Transport of China
文摘The class of bi-directional optimal velocity models can describe the bi-directional looking effect that usually exists in the reality and is even enhanced with the development of the connected vehicle technologies. Its combined string stability condition can be obtained through the method of the ring-road based string stability analysis. However, the partial string stability about traffic fluctuation propagated backward or forward was neglected, which will be analyzed in detail in this work by the method of transfer function and its H∞ norm from the viewpoint of control theory. Then, through comparing the conditions of combined and partial string stabilities, their relationships can make traffic flow be divided into three distinguishable regions, displaying various combined and partial string stability performance. Finally, the numerical experiments verify the theoretical results and find that the final displaying string stability or instability performance results from the accumulated and offset effects of traffic fluctuations propagated from different directions.
基金supported by the National Natural Science Foundation for Young Scientists of China(61201190)
文摘Vehicle positioning with the global navigation satellite system （GNSS） in urban environments faces two problems which are attenuation and dynamic. For traditional GNSS receivers hardly able to track dynamic weak signals, the coupling between all visible satellite signals is ignored in the absence of navigation state feedback, and thermal noise error and dynamic stress threshold are contradictory due to non-coherent discriminators. The vector delay/frequency locked loop （VDFLL） with navigation state feedback and the joint vector tracking loop （JVTL） with coherent discriminator which is a synchronization parameter tracking loop based on maximum likelihood estimation （MLE） are proposed to improve the tracking sensitivity of GNSS receiver in dynamic weak signal environments. A joint vector position tracking loop （JVPTL） directly tracking user position and velocity is proposed to further improve tracking sensitivity. The coherent navigation parameter discriminator of JVPTL, being able to ease the contradiction between thermal noise error and dynamic stress threshold, is based on MLE according to the navigation parameter based linear model of received baseband signals. Simulation results show that JVPTL, which combines the advantages of both VDFLL and JVTL, performs better than both VDFLL and JVTL in dynamic weak signal environments.
基金Project(50809058)supported by the National Natural Science Foundation of China
文摘A knowledge-based network for Section Yidong Bridge,Dongyang River,one tributary of Qiantang River,Zhejiang Province,China,is established in order to model water quality in areas under small data.Then,based on normal transformation of variables with routine monitoring data and normal assumption of variables without routine monitoring data,a conditional linear Gaussian Bayesian network is constructed.A "two-constraint selection" procedure is proposed to estimate potential parameter values under small data.Among all potential parameter values,the ones that are most probable are selected as the "representatives".Finally,the risks of pollutant concentration exceeding national water quality standards are calculated and pollution reduction decisions for decision-making reference are proposed.The final results show that conditional linear Gaussian Bayesian network and "two-constraint selection" procedure are very useful in evaluating risks when there is limited data and can help managers to make sound decisions under small data.
文摘The adaptive neuro-fuzzy inference systems(ANFIS)are widely used in the concrete technology.In this research,the compressive strength of light weight concrete was determined.To this end,the scoria percentage and curing day variables were used as the input parameters,and compressive strength and tensile strength were used as the output parameters.In addition,100 patterns were used,70%of which were used for training and 30%were used for testing.To assess the precision of the neuro-fuzzy system,it was compared using two linear regression models.The comparisons were carried out in the training and testing phases.Research results revealed that the neuro-fuzzy systems model offers more potential,flexibility,and precision than the statistical models.
文摘Many products always operate under various complex environment conditions. To describe the dynamic influence of environment factors on their reliability, a method of reliability sensitivity analysis is proposed. In this method, the location parameter is assumed as a function of relevant environment variables while the scale parameter is assumed as an unknown positive constant. Then, the location parameter function is constructed by using the method of radial basis function. Using the varied environment test data, the log-likelihood function is transformed to a generalized linear expression by describing the indicator as Poisson variable. With the generalized linear model, the maximum likelihood estimations of the model coefficients are obtained. With the reliability model, the reliability sensitivity is obtained. An instance analysis shows that the method is feasible to analyze the dynamic variety characters of reliability along with environment factors and is straightforward for engineering application.
基金supported by the National High Technology Research and Development Program of China (863 Program) (2007AA04Z227)
文摘This paper proposes a robust method of parameter estimation and data classification for multiple-structural data based on the linear error in variable（EIV） model.The traditional EIV model fitting problem is analyzed and a robust growing algorithm is developed to extract the underlying linear structure of the observed data.Under the structural density assumption,the C-step technique borrowed from the Rousseeuw＇s robust MCD estimator is used to keep the algorithm robust and the mean-shift algorithm is adopted to ensure a good initialization.To eliminate the model ambiguities of the multiple-structural data,statistical hypotheses tests are used to refine the data classification and improve the accuracy of the model parameter estimation.Experiments show that the efficiency and robustness of the proposed algorithm.
