For many dam projects in China, the 50-year designed life time is coming to an end. It is urgent to study the theory and method to evaluate the dam service life. In this paper, firstly, the probability theory of fuzzy...For many dam projects in China, the 50-year designed life time is coming to an end. It is urgent to study the theory and method to evaluate the dam service life. In this paper, firstly, the probability theory of fuzzy event and time-varying effect theory are used to analyze the time-variety of various risk factors in the process of dam operations. A method is proposed to quantify the above time-variety and a model to describe the fuzzy time-varying risk probability for the dam structure is also built. Secondly, the information entropy theory is used to analyze the uncertain degree relationship between the characteristic value of membership function and fuzzy risk probability, and a mathematical method is presented to calculate the time-varying risk probability accordingly. Thirdly, the relation mode between time-varying risk probability and service life is discussed. Based on this relation mode and the acceptable risk probability of dams in China, a method is put forward to evaluate and forecast the dam service life. Finally, the proposed theory and method are used to analyze one concrete dam. The dynamic variability and mutation feature of the dam risk probability are analyzed. The remaining service life of this dam is forecasted. The obtained results can provide technology support for the project management department to make treatment measures of engineering and reasonably arrange reinforce cost. The principles in this paper have wide applicability and can be used in risk analysis for slope instability and other fields.展开更多
To solve the problem of attitude tracking of a rigid spacecraft with an either known or measurable desired attitude trajectory, three types of time-varying sliding mode controls are introduced under consideration of c...To solve the problem of attitude tracking of a rigid spacecraft with an either known or measurable desired attitude trajectory, three types of time-varying sliding mode controls are introduced under consideration of control input constraints. The sliding surfaces of the three types initially pass arbitrary initial values of the system, and then shift or rotate to reach predetermined ones. This way, the system trajectories are always on the sliding surfaces, and the system work is guaranteed to have robustness against parameter uncertainty and external disturbances all the time. The controller parameters are optimized by means of genetic algorithm to minimize the index consisting of the weighted index of squared error （ISE） of the system and the weighted penalty term of violation of control input constraint. The stability is verified with Lyapunov method. Compared with the conventional sliding mode control, simulation results show the proposed algorithm having better robustness against inertia matrix uncertainty and external disturbance torques.展开更多
This paper proposes a new adaptive iterative learning control approach for a class of nonlinearly parameterized systems with unknown time-varying delay and unknown control direction.By employing the parameter separati...This paper proposes a new adaptive iterative learning control approach for a class of nonlinearly parameterized systems with unknown time-varying delay and unknown control direction.By employing the parameter separation technique and signal replacement mechanism,the approach can overcome unknown time-varying parameters and unknown time-varying delay of the nonlinear systems.By incorporating a Nussbaum-type function,the proposed approach can deal with the unknown control direction of the nonlinear systems.Based on a Lyapunov-Krasovskii-like composite energy function,the convergence of tracking error sequence is achieved in the iteration domain.Finally,two simulation examples are provided to illustrate the feasibility of the proposed control method.展开更多
Appropriate modeling for a controlled plant has been a remarkable problem in the control field. A new modeling theory, i.e. characteristic modeling, is roundly demonstrated. It is deduced in detail that a general line...Appropriate modeling for a controlled plant has been a remarkable problem in the control field. A new modeling theory, i.e. characteristic modeling, is roundly demonstrated. It is deduced in detail that a general linear constant high-order system can be equivalently described with a two-order time-varying difference equation. The application of the characteristic modeling method to the control of flexible structure is also introduced. Especially, as an example, the Hubble Space Telescope is used to illustrate the application of the characteristic modeling and adaptive control method proposed in this paper.展开更多
The fifth generation(5G) network is expected to support significantly large amount of mobile data traffic and huge number of wireless connections,to achieve better spectrum- and energy-efficiency,as well as quality of...The fifth generation(5G) network is expected to support significantly large amount of mobile data traffic and huge number of wireless connections,to achieve better spectrum- and energy-efficiency,as well as quality of service(QoS) in terms of delay,reliability and security.Furthermore,the 5G network shall also incorporate high mobility requirements as an integral part,providing satisfactory service to users travelling at a speed up to 500 km/h.This paper provides a survey of potential high mobility wireless communication(HMWC) techniques for 5G network.After discussing the typical requirements and challenges of HMWC,key techniques to cope with the challenges are reviewed,including transmission techniques under the fast timevarying channels,network architecture with mobility support,and mobility management.Finally,future research directions on 5G high mobility communications are given.展开更多
When used for separating multi-component non-stationary signals, the adaptive time-varying filter(ATF) based on multi-scale chirplet sparse signal decomposition(MCSSD) generates phase shift and signal distortion. To o...When used for separating multi-component non-stationary signals, the adaptive time-varying filter(ATF) based on multi-scale chirplet sparse signal decomposition(MCSSD) generates phase shift and signal distortion. To overcome this drawback, the zero phase filter is introduced to the mentioned filter, and a fault diagnosis method for speed-changing gearbox is proposed. Firstly, the gear meshing frequency of each gearbox is estimated by chirplet path pursuit. Then, according to the estimated gear meshing frequencies, an adaptive zero phase time-varying filter(AZPTF) is designed to filter the original signal. Finally, the basis for fault diagnosis is acquired by the envelope order analysis to the filtered signal. The signal consisting of two time-varying amplitude modulation and frequency modulation(AM-FM) signals is respectively analyzed by ATF and AZPTF based on MCSSD. The simulation results show the variances between the original signals and the filtered signals yielded by AZPTF based on MCSSD are 13.67 and 41.14, which are far less than variances (323.45 and 482.86) between the original signals and the filtered signals obtained by ATF based on MCSSD. The experiment results on the vibration signals of gearboxes indicate that the vibration signals of the two speed-changing gearboxes installed on one foundation bed can be separated by AZPTF effectively. Based on the demodulation information of the vibration signal of each gearbox, the fault diagnosis can be implemented. Both simulation and experiment examples prove that the proposed filter can extract a mono-component time-varying AM-FM signal from the multi-component time-varying AM-FM signal without distortion.展开更多
In this paper, we develop a unique time-varying forecasting model for dynamic demand of medical resources based on a susceptible-exposed-infected-recovered （SEIR） influenza diffusion model. In this forecasting mecha...In this paper, we develop a unique time-varying forecasting model for dynamic demand of medical resources based on a susceptible-exposed-infected-recovered （SEIR） influenza diffusion model. In this forecasting mechanism, medical resources allocated in the early period will take effect in subduing the spread of influenza and thus impact the demand in the later period. We adopt a discrete time-space network to describe the medical resources allocation process following a hypothetical influenza outbreak in a region. The entire medical resources allocation process is constructed as a multi-stage integer programming problem. At each stage, we solve a cost minimization sub-problem subject to the time-varying demand. The corresponding optimal allocation result is then used as an input to the control process of influenza spread, which in turn determines the demand for the next stage. In addition, we present a comparison between the proposed model and an empirical model. Our results could help decision makers prepare for a pandemic, including how to allocate limited resources dynamically.展开更多
基金Supported by the National Natural Science Foundation of China(Grant Nos.50809025,50539110,50539010,50539030)the Science and Technology Sup-port Plan(Grant Nos.2008BAB29B03,2006BAC14B03)
文摘For many dam projects in China, the 50-year designed life time is coming to an end. It is urgent to study the theory and method to evaluate the dam service life. In this paper, firstly, the probability theory of fuzzy event and time-varying effect theory are used to analyze the time-variety of various risk factors in the process of dam operations. A method is proposed to quantify the above time-variety and a model to describe the fuzzy time-varying risk probability for the dam structure is also built. Secondly, the information entropy theory is used to analyze the uncertain degree relationship between the characteristic value of membership function and fuzzy risk probability, and a mathematical method is presented to calculate the time-varying risk probability accordingly. Thirdly, the relation mode between time-varying risk probability and service life is discussed. Based on this relation mode and the acceptable risk probability of dams in China, a method is put forward to evaluate and forecast the dam service life. Finally, the proposed theory and method are used to analyze one concrete dam. The dynamic variability and mutation feature of the dam risk probability are analyzed. The remaining service life of this dam is forecasted. The obtained results can provide technology support for the project management department to make treatment measures of engineering and reasonably arrange reinforce cost. The principles in this paper have wide applicability and can be used in risk analysis for slope instability and other fields.
文摘To solve the problem of attitude tracking of a rigid spacecraft with an either known or measurable desired attitude trajectory, three types of time-varying sliding mode controls are introduced under consideration of control input constraints. The sliding surfaces of the three types initially pass arbitrary initial values of the system, and then shift or rotate to reach predetermined ones. This way, the system trajectories are always on the sliding surfaces, and the system work is guaranteed to have robustness against parameter uncertainty and external disturbances all the time. The controller parameters are optimized by means of genetic algorithm to minimize the index consisting of the weighted index of squared error （ISE） of the system and the weighted penalty term of violation of control input constraint. The stability is verified with Lyapunov method. Compared with the conventional sliding mode control, simulation results show the proposed algorithm having better robustness against inertia matrix uncertainty and external disturbance torques.
基金supported by National Natural Science Foundation of China (No. 60974139)Fundamental Research Funds for the Central Universities (No. 72103676)
文摘This paper proposes a new adaptive iterative learning control approach for a class of nonlinearly parameterized systems with unknown time-varying delay and unknown control direction.By employing the parameter separation technique and signal replacement mechanism,the approach can overcome unknown time-varying parameters and unknown time-varying delay of the nonlinear systems.By incorporating a Nussbaum-type function,the proposed approach can deal with the unknown control direction of the nonlinear systems.Based on a Lyapunov-Krasovskii-like composite energy function,the convergence of tracking error sequence is achieved in the iteration domain.Finally,two simulation examples are provided to illustrate the feasibility of the proposed control method.
基金This paper was supported by the National Natural Science Foundation of China (Grant No. 60034010) .
文摘Appropriate modeling for a controlled plant has been a remarkable problem in the control field. A new modeling theory, i.e. characteristic modeling, is roundly demonstrated. It is deduced in detail that a general linear constant high-order system can be equivalently described with a two-order time-varying difference equation. The application of the characteristic modeling method to the control of flexible structure is also introduced. Especially, as an example, the Hubble Space Telescope is used to illustrate the application of the characteristic modeling and adaptive control method proposed in this paper.
基金supported by the National Basic Research Program of China (973 Program No.2012CB316100)
文摘The fifth generation(5G) network is expected to support significantly large amount of mobile data traffic and huge number of wireless connections,to achieve better spectrum- and energy-efficiency,as well as quality of service(QoS) in terms of delay,reliability and security.Furthermore,the 5G network shall also incorporate high mobility requirements as an integral part,providing satisfactory service to users travelling at a speed up to 500 km/h.This paper provides a survey of potential high mobility wireless communication(HMWC) techniques for 5G network.After discussing the typical requirements and challenges of HMWC,key techniques to cope with the challenges are reviewed,including transmission techniques under the fast timevarying channels,network architecture with mobility support,and mobility management.Finally,future research directions on 5G high mobility communications are given.
基金supported by National Natural Science Foundation of China (Grant No. 71271078)National Hi-tech Research and Development Program of China (863 Program, Grant No. 2009AA04Z414)Integration of Industry, Education and Research of Guangdong Province, and Ministry of Education of China (Grant No. 2009B090300312)
文摘When used for separating multi-component non-stationary signals, the adaptive time-varying filter(ATF) based on multi-scale chirplet sparse signal decomposition(MCSSD) generates phase shift and signal distortion. To overcome this drawback, the zero phase filter is introduced to the mentioned filter, and a fault diagnosis method for speed-changing gearbox is proposed. Firstly, the gear meshing frequency of each gearbox is estimated by chirplet path pursuit. Then, according to the estimated gear meshing frequencies, an adaptive zero phase time-varying filter(AZPTF) is designed to filter the original signal. Finally, the basis for fault diagnosis is acquired by the envelope order analysis to the filtered signal. The signal consisting of two time-varying amplitude modulation and frequency modulation(AM-FM) signals is respectively analyzed by ATF and AZPTF based on MCSSD. The simulation results show the variances between the original signals and the filtered signals yielded by AZPTF based on MCSSD are 13.67 and 41.14, which are far less than variances (323.45 and 482.86) between the original signals and the filtered signals obtained by ATF based on MCSSD. The experiment results on the vibration signals of gearboxes indicate that the vibration signals of the two speed-changing gearboxes installed on one foundation bed can be separated by AZPTF effectively. Based on the demodulation information of the vibration signal of each gearbox, the fault diagnosis can be implemented. Both simulation and experiment examples prove that the proposed filter can extract a mono-component time-varying AM-FM signal from the multi-component time-varying AM-FM signal without distortion.
基金partially supported by the National Natural Science Foundation of China (No.71301076,71401075)Natural Science Foundation of Jiangsu Province(BK20130771)+1 种基金the Research Fund for the Doctoral Program of Higher Education of China(20133219120037)the Zijin Intelligent Program(No. 2013-ZJ0211) of Nanjing University of Science and Technology
文摘In this paper, we develop a unique time-varying forecasting model for dynamic demand of medical resources based on a susceptible-exposed-infected-recovered （SEIR） influenza diffusion model. In this forecasting mechanism, medical resources allocated in the early period will take effect in subduing the spread of influenza and thus impact the demand in the later period. We adopt a discrete time-space network to describe the medical resources allocation process following a hypothetical influenza outbreak in a region. The entire medical resources allocation process is constructed as a multi-stage integer programming problem. At each stage, we solve a cost minimization sub-problem subject to the time-varying demand. The corresponding optimal allocation result is then used as an input to the control process of influenza spread, which in turn determines the demand for the next stage. In addition, we present a comparison between the proposed model and an empirical model. Our results could help decision makers prepare for a pandemic, including how to allocate limited resources dynamically.
