This paper studies the problem of robust H∞ control of piecewise-linear chaotic systems with random data loss. The communication links between the plant and the controller are assumed to be imperfect （that is, data ...This paper studies the problem of robust H∞ control of piecewise-linear chaotic systems with random data loss. The communication links between the plant and the controller are assumed to be imperfect （that is, data loss occurs intermittently, which appears typically in a network environment）. The data loss is modelled as a random process which obeys a Bernoulli distribution. In the face of random data loss, a piecewise controller is designed to robustly stabilize the networked system in the sense of mean square and also achieve a prescribed H∞ disturbance attenuation performance based on a piecewise-quadratic Lyapunov function. The required H∞ controllers can be designed by solving a set of linear matrix inequalities （LMIs）. Chua＇s system is provided to illustrate the usefulness and applicability of the developed theoretical results.展开更多
This paper discusses the model-based predictive controller design of networked nonlinear systems with communica- tion delay and data loss. Based on the analysis of the closed-loop networked predictive control systems,...This paper discusses the model-based predictive controller design of networked nonlinear systems with communica- tion delay and data loss. Based on the analysis of the closed-loop networked predictive control systems, the model-based networked predictive control strategy can compensate for communication delay and data loss in an active way. The designed model-based predictive controller can also guarantee the stability of the closed-loop networked system. The simulation re- suits demonstrate the feasibility and efficacy of the proposed model-based predictive controller design scheme.展开更多
The purpose of this article is to investigate the second-order P-type iterative learning control(ILC)scheme in the presence of data loss for a class of linear discrete-time switched systems with disturbances.Employing...The purpose of this article is to investigate the second-order P-type iterative learning control(ILC)scheme in the presence of data loss for a class of linear discrete-time switched systems with disturbances.Employing the super-vector representation technique,the discrete-time linear switched system is reformulated as an input-output transmission equation.The robustness of the resulting switched system driven by a second-order P-type ILC scheme is guaranteed through the use of the super-vector representation technique.Importantly,the article also explores cases of data loss occurring during data transmission.The proposed methodology exhibits significantly improved convergence performance compared to the P-type ILC scheme(Yang et al.,2022,Robust finite-iteration tracking of discrete-time systems in repetitive process setting via ILC scheme.International Journal of Robust and Nonlinear Control,32(5),2585-2602.https://doi.org/10.1002/rnc.5782).Simulation examples are provided to demonstrate the effectiveness of the proposed scheme.展开更多
This paper considers the tracking control problem of a wheeled mobile robot under situation of communication delay and consecutive data packet dropouts in the feedback channel. A tracking controller in discrete-time d...This paper considers the tracking control problem of a wheeled mobile robot under situation of communication delay and consecutive data packet dropouts in the feedback channel. A tracking controller in discrete-time domain for the case of ideal network condition is first derived, and then the networked predictive controller as well as two algorithms for dealing with communication delay and consecutive data packet dropouts are proposed. Simulation and experimental results verify the realizability and effectiveness of the proposed algorithms.展开更多
The paper analyses the improvement of track loss in clutter with multisensor data fusion.By a determination of the transition probability density function for the fusion prediction error, one can study the mechanism o...The paper analyses the improvement of track loss in clutter with multisensor data fusion.By a determination of the transition probability density function for the fusion prediction error, one can study the mechanism of track loss analytically. With nearest-neighbor association algorithm. The paper we studies the fused tracking performance parameters, such as mean time to lose fused track and the cumulative probability of lost fused track versus the normalized clutter density, for track continuation and track initiation, respectively. A comparison of the results obtained with the case of a single sensor is presented. These results show that the fused tracks of multisensor reduce the possibility of track loss and improve the tracking performance. The analysis is of great importance for further understanding the action of data fusion.展开更多
Nowadays, the technology of renewable sources grid-connection and DC transmission has a rapid development. And phasor measurement units(PMUs) become more notable in power grids, due to the necessary of real time monit...Nowadays, the technology of renewable sources grid-connection and DC transmission has a rapid development. And phasor measurement units(PMUs) become more notable in power grids, due to the necessary of real time monitoring and close-loop control applications. However, the PMUs data quality issue affects applications based on PMUs a lot. This paper proposes a simple yet effective method for recovering PMU data. To simply the issue, two different scenarios of PMUs data loss are first defined. Then a key combination of preferred selection strategies is introduced. And the missing data is recovered by the function of spline interpolation. This method has been tested by artificial data and field data obtained from on-site PMUs. The results demonstrate that the proposed method recovers the missing PMU data quickly and accurately. And it is much better than other methods when missing data are massive and continuous. This paper also presents the interesting direction for future work.展开更多
According to relevant data statistics, each year, nearly 70% of users have disc data loss because of misuse, viral damage, physical damage and hardware failure, bringing irreparable damage to enterprises, institutions...According to relevant data statistics, each year, nearly 70% of users have disc data loss because of misuse, viral damage, physical damage and hardware failure, bringing irreparable damage to enterprises, institutions and individuals. So data recovery technology has attracted wide attention of users and how to use data recovery technology to help to recover lost data and to minimize the loss has become an urgent need. This paper starts from the software and hardware failure to analyze two aspects of hard disk data loss, data storage structure theory, and combined with practical experience, it elaborates data damage type and related recovery methods.展开更多
Data fusion can effectively process multi-sensor information to obtain more accurate and reliable results than a single sensor.The data of water quality in the environment comes from different sensors,thus the data mu...Data fusion can effectively process multi-sensor information to obtain more accurate and reliable results than a single sensor.The data of water quality in the environment comes from different sensors,thus the data must be fused.In our research,self-adaptive weighted data fusion method is used to respectively integrate the data from the PH value,temperature,oxygen dissolved and NH3 concentration of water quality environment.Based on the fusion,the Grubbs method is used to detect the abnormal data so as to provide data support for estimation,prediction and early warning of the water quality.展开更多
Cochlodinium polykrikoides is a notoriously harmful algal species that inflicts severe damage on the aquacultures of the coastal seas of Korea and Japan. Information on their expected movement tracks and boundaries of...Cochlodinium polykrikoides is a notoriously harmful algal species that inflicts severe damage on the aquacultures of the coastal seas of Korea and Japan. Information on their expected movement tracks and boundaries of influence is very useful and important for the effective establishment of a reduction plan. In general, the information is supported by a red-tide（a.k.a algal bloom） model. The performance of the model is highly dependent on the accuracy of parameters, which are the coefficients of functions approximating the biological growth and loss patterns of the C. polykrikoides. These parameters have been estimated using the bioassay data composed of growth-limiting factor and net growth rate value pairs. In the case of the C. polykrikoides, the parameters are different from each other in accordance with the used data because the bioassay data are sufficient compared to the other algal species. The parameters estimated by one specific dataset can be viewed as locally-optimized because they are adjusted only by that dataset. In cases where the other one data set is used, the estimation error might be considerable. In this study, the parameters are estimated by all available data sets without the use of only one specific data set and thus can be considered globally optimized. The cost function for the optimization is defined as the integrated mean squared estimation error, i.e., the difference between the values of the experimental and estimated rates. Based on quantitative error analysis, the root-mean squared errors of the global parameters show smaller values, approximately 25%–50%, than the values of the local parameters. In addition, bias is removed completely in the case of the globally estimated parameters. The parameter sets can be used as the reference default values of a red-tide model because they are optimal and representative. However, additional tuning of the parameters using the in-situ monitoring data is highly required.As opposed to the bioassay data, it is necessary because the bioassay data have limitations in terms of the in-situ coastal conditions.展开更多
基金Project partially supported by the Young Scientists Fund of the National Natural Science Foundation of China(Grant No.60904004)the Key Youth Science and Technology Foundation of University of Electronic Science and Technology of China (Grant No.L08010201JX0720)
文摘This paper studies the problem of robust H∞ control of piecewise-linear chaotic systems with random data loss. The communication links between the plant and the controller are assumed to be imperfect （that is, data loss occurs intermittently, which appears typically in a network environment）. The data loss is modelled as a random process which obeys a Bernoulli distribution. In the face of random data loss, a piecewise controller is designed to robustly stabilize the networked system in the sense of mean square and also achieve a prescribed H∞ disturbance attenuation performance based on a piecewise-quadratic Lyapunov function. The required H∞ controllers can be designed by solving a set of linear matrix inequalities （LMIs）. Chua＇s system is provided to illustrate the usefulness and applicability of the developed theoretical results.
基金Project supported by the Key Program for the National Natural Science Foundation of China(Grant No.61333003)the General Program for the National Natural Science Foundation of China(Grant No.61273104)
文摘This paper discusses the model-based predictive controller design of networked nonlinear systems with communica- tion delay and data loss. Based on the analysis of the closed-loop networked predictive control systems, the model-based networked predictive control strategy can compensate for communication delay and data loss in an active way. The designed model-based predictive controller can also guarantee the stability of the closed-loop networked system. The simulation re- suits demonstrate the feasibility and efficacy of the proposed model-based predictive controller design scheme.
基金supported by University Grants Commission[19-06-2016(i)EU-V(434954)].
文摘The purpose of this article is to investigate the second-order P-type iterative learning control(ILC)scheme in the presence of data loss for a class of linear discrete-time switched systems with disturbances.Employing the super-vector representation technique,the discrete-time linear switched system is reformulated as an input-output transmission equation.The robustness of the resulting switched system driven by a second-order P-type ILC scheme is guaranteed through the use of the super-vector representation technique.Importantly,the article also explores cases of data loss occurring during data transmission.The proposed methodology exhibits significantly improved convergence performance compared to the P-type ILC scheme(Yang et al.,2022,Robust finite-iteration tracking of discrete-time systems in repetitive process setting via ILC scheme.International Journal of Robust and Nonlinear Control,32(5),2585-2602.https://doi.org/10.1002/rnc.5782).Simulation examples are provided to demonstrate the effectiveness of the proposed scheme.
基金supported in part by the National Natural Science Foundation of China under Grant Nos.61333033,61690210 and 61690212
文摘This paper considers the tracking control problem of a wheeled mobile robot under situation of communication delay and consecutive data packet dropouts in the feedback channel. A tracking controller in discrete-time domain for the case of ideal network condition is first derived, and then the networked predictive controller as well as two algorithms for dealing with communication delay and consecutive data packet dropouts are proposed. Simulation and experimental results verify the realizability and effectiveness of the proposed algorithms.
文摘The paper analyses the improvement of track loss in clutter with multisensor data fusion.By a determination of the transition probability density function for the fusion prediction error, one can study the mechanism of track loss analytically. With nearest-neighbor association algorithm. The paper we studies the fused tracking performance parameters, such as mean time to lose fused track and the cumulative probability of lost fused track versus the normalized clutter density, for track continuation and track initiation, respectively. A comparison of the results obtained with the case of a single sensor is presented. These results show that the fused tracks of multisensor reduce the possibility of track loss and improve the tracking performance. The analysis is of great importance for further understanding the action of data fusion.
基金supported in part by National Natural Science Foundation of China(NSFC)(51627811,51707064)Project Supported by the National Key Research and Development Program of China(2017YFB090204)Project of State Grid Corporation of China(SGTYHT/16-JS-198)
文摘Nowadays, the technology of renewable sources grid-connection and DC transmission has a rapid development. And phasor measurement units(PMUs) become more notable in power grids, due to the necessary of real time monitoring and close-loop control applications. However, the PMUs data quality issue affects applications based on PMUs a lot. This paper proposes a simple yet effective method for recovering PMU data. To simply the issue, two different scenarios of PMUs data loss are first defined. Then a key combination of preferred selection strategies is introduced. And the missing data is recovered by the function of spline interpolation. This method has been tested by artificial data and field data obtained from on-site PMUs. The results demonstrate that the proposed method recovers the missing PMU data quickly and accurately. And it is much better than other methods when missing data are massive and continuous. This paper also presents the interesting direction for future work.
文摘According to relevant data statistics, each year, nearly 70% of users have disc data loss because of misuse, viral damage, physical damage and hardware failure, bringing irreparable damage to enterprises, institutions and individuals. So data recovery technology has attracted wide attention of users and how to use data recovery technology to help to recover lost data and to minimize the loss has become an urgent need. This paper starts from the software and hardware failure to analyze two aspects of hard disk data loss, data storage structure theory, and combined with practical experience, it elaborates data damage type and related recovery methods.
基金This study was supported by National Key Research and Development Project(Project No.2017YFD0301506)National Social Science Foundation(Project No.71774052)+1 种基金Hunan Education Department Scientific Research Project(Project No.17K04417A092).
文摘Data fusion can effectively process multi-sensor information to obtain more accurate and reliable results than a single sensor.The data of water quality in the environment comes from different sensors,thus the data must be fused.In our research,self-adaptive weighted data fusion method is used to respectively integrate the data from the PH value,temperature,oxygen dissolved and NH3 concentration of water quality environment.Based on the fusion,the Grubbs method is used to detect the abnormal data so as to provide data support for estimation,prediction and early warning of the water quality.
基金The part of the project "Development of Korea Operational Oceanographic System(KOOS),Phase 2",funded by the Ministry of Oceans and Fisheries,Koreathe part of the project entitled "Cooperative Project on Korea-China Bilateral Committee on Ocean Science",funded by the Ministry of Oceans and Fisheries,Korea and China-Korea Joint Research Ocean Research Center
文摘Cochlodinium polykrikoides is a notoriously harmful algal species that inflicts severe damage on the aquacultures of the coastal seas of Korea and Japan. Information on their expected movement tracks and boundaries of influence is very useful and important for the effective establishment of a reduction plan. In general, the information is supported by a red-tide（a.k.a algal bloom） model. The performance of the model is highly dependent on the accuracy of parameters, which are the coefficients of functions approximating the biological growth and loss patterns of the C. polykrikoides. These parameters have been estimated using the bioassay data composed of growth-limiting factor and net growth rate value pairs. In the case of the C. polykrikoides, the parameters are different from each other in accordance with the used data because the bioassay data are sufficient compared to the other algal species. The parameters estimated by one specific dataset can be viewed as locally-optimized because they are adjusted only by that dataset. In cases where the other one data set is used, the estimation error might be considerable. In this study, the parameters are estimated by all available data sets without the use of only one specific data set and thus can be considered globally optimized. The cost function for the optimization is defined as the integrated mean squared estimation error, i.e., the difference between the values of the experimental and estimated rates. Based on quantitative error analysis, the root-mean squared errors of the global parameters show smaller values, approximately 25%–50%, than the values of the local parameters. In addition, bias is removed completely in the case of the globally estimated parameters. The parameter sets can be used as the reference default values of a red-tide model because they are optimal and representative. However, additional tuning of the parameters using the in-situ monitoring data is highly required.As opposed to the bioassay data, it is necessary because the bioassay data have limitations in terms of the in-situ coastal conditions.
