This paper presents a Fault Mode Probability Factor(FMPF) based Fault-Tolerant Control(FTC) strategy for multiple faults of Dissimilar Redundant Actuation System(DRAS)composed of Hydraulic Actuator(HA) and Ele...This paper presents a Fault Mode Probability Factor(FMPF) based Fault-Tolerant Control(FTC) strategy for multiple faults of Dissimilar Redundant Actuation System(DRAS)composed of Hydraulic Actuator(HA) and Electro-Hydrostatic Actuator(EHA). The long-term service and severe working conditions can result in multiple gradual faults which can ultimately degrade the system performance, resulting in the system model drift into the fault state characterized with parameter uncertainty. The paper proposes to address this problem by using the historical statistics of the multiple gradual faults and the proposed FMPF to amend the system model with parameter uncertainty. To balance the system model precision and computation time, a Moving Window(MW) method is used to determine the applied historical statistics. The FMPF based FTC strategy is developed for the amended system model where the system estimation and Linear Quadratic Regulator(LQR) are updated at the end of system sampling period. The simulations of DRAS system subjected to multiple faults have been performed and the results indicate the effectiveness of the proposed approach.展开更多
The problem of identification of friend-or-foe aircraft in the actual application condition is addressed.A hybrid algorithm combining fuzzy neutral network with probability factor(FNNP),multi-level fuzzy comprehensi...The problem of identification of friend-or-foe aircraft in the actual application condition is addressed.A hybrid algorithm combining fuzzy neutral network with probability factor(FNNP),multi-level fuzzy comprehensive evaluation and the DempsterShafer(D-S) theory is proposed.This hybrid algorithm constructs a complete process from generating the fuzzy database to the final identification,realizes the identification of friend-or-foe automatically if the training samples or expert’s experience can be obtained,and reduces the effect of uncertainties in the process of identification.At the same time,the whole algorithm can update the identification result with the augment of observations.The performance of the proposed algorithm is assessed by simulations.Results show that the proposed algorithm can successfully deduce the aircraft’s identity even if the observations have measurement errors.展开更多
With the rapid development of the Internet,the amount of data recorded on the Internet has increased dramatically.It is becoming more and more urgent to effectively obtain the specific information we need from the vas...With the rapid development of the Internet,the amount of data recorded on the Internet has increased dramatically.It is becoming more and more urgent to effectively obtain the specific information we need from the vast ocean of data.In this study,we propose a novel collaborative filtering algorithm for generating recommendations in e-commerce.This study has two main innovations.First,we propose a mechanismthat embeds temporal behavior information to find a neighbor set in which each neighbor has a very significant impact on the current user or item.Second,we propose a novel collaborative filtering algorithm by injecting the neighbor set into probability matrix factorization.We compared the proposed method with several state-of-the-art alternatives on real datasets.The experimental results show that our proposed method outperforms the prevailing approaches.展开更多
基金co-supported by the National Natural Science Foundation of China(Nos.51620105010,51675019 and 51575019)the National Basic Research Program of China(No.2014CB046402)+1 种基金the Fundamental Research Funds for the Central Universities of China(YWF-17-BJ-Y-105)the "111" Project of China
文摘This paper presents a Fault Mode Probability Factor(FMPF) based Fault-Tolerant Control(FTC) strategy for multiple faults of Dissimilar Redundant Actuation System(DRAS)composed of Hydraulic Actuator(HA) and Electro-Hydrostatic Actuator(EHA). The long-term service and severe working conditions can result in multiple gradual faults which can ultimately degrade the system performance, resulting in the system model drift into the fault state characterized with parameter uncertainty. The paper proposes to address this problem by using the historical statistics of the multiple gradual faults and the proposed FMPF to amend the system model with parameter uncertainty. To balance the system model precision and computation time, a Moving Window(MW) method is used to determine the applied historical statistics. The FMPF based FTC strategy is developed for the amended system model where the system estimation and Linear Quadratic Regulator(LQR) are updated at the end of system sampling period. The simulations of DRAS system subjected to multiple faults have been performed and the results indicate the effectiveness of the proposed approach.
文摘The problem of identification of friend-or-foe aircraft in the actual application condition is addressed.A hybrid algorithm combining fuzzy neutral network with probability factor(FNNP),multi-level fuzzy comprehensive evaluation and the DempsterShafer(D-S) theory is proposed.This hybrid algorithm constructs a complete process from generating the fuzzy database to the final identification,realizes the identification of friend-or-foe automatically if the training samples or expert’s experience can be obtained,and reduces the effect of uncertainties in the process of identification.At the same time,the whole algorithm can update the identification result with the augment of observations.The performance of the proposed algorithm is assessed by simulations.Results show that the proposed algorithm can successfully deduce the aircraft’s identity even if the observations have measurement errors.
基金supported by the National Natural Science Foundation of China under Grant Nos.81873915,61702225 and 61806026Ministry of Science and Technology Key Research and Development Program of China under Grant No.2018YFC0116902+3 种基金by the Natural Science Foundation of Jiangsu Province under Grant No.BK20180956by the 2018 Six Talent Peaks Project of Jiangsu Province under Grant No.XYDXX-127by the Science and Technology demonstration project of social development of Wuxi under Grant WX18IVJN002by the Philosophy and Social Science Foundation of Jiangsu Province(18YSC009).
文摘With the rapid development of the Internet,the amount of data recorded on the Internet has increased dramatically.It is becoming more and more urgent to effectively obtain the specific information we need from the vast ocean of data.In this study,we propose a novel collaborative filtering algorithm for generating recommendations in e-commerce.This study has two main innovations.First,we propose a mechanismthat embeds temporal behavior information to find a neighbor set in which each neighbor has a very significant impact on the current user or item.Second,we propose a novel collaborative filtering algorithm by injecting the neighbor set into probability matrix factorization.We compared the proposed method with several state-of-the-art alternatives on real datasets.The experimental results show that our proposed method outperforms the prevailing approaches.