Abstract--This paper conducts a survey on iterative learn- ing control （ILC） with incomplete information and associated control system design, which is a frontier of the ILC field. The incomplete information, includ...Abstract--This paper conducts a survey on iterative learn- ing control （ILC） with incomplete information and associated control system design, which is a frontier of the ILC field. The incomplete information, including passive and active types, can cause data loss or fragment due to various factors. Passive incomplete information refers to incomplete data and information caused by practical system limitations during data collection, storage, transmission, and processing, such as data dropouts, delays, disordering, and limited transmission bandwidth. Active incomplete information refers to incomplete data and information caused by man-made reduction of data quantity and quality on the premise that the given objective is satisfied, such as sampling and quantization. This survey emphasizes two aspects： the first one is how to guarantee good learning performance and tracking performance with passive incomplete data, and the second is how to balance the control performance index and data demand by active means. The promising research directions along this topic are also addressed, where data robustness is highly emphasized. This survey is expected to improve understanding of the restrictive relationship and trade-off between incomplete data and tracking performance, quantitatively, and promote further developments of ILC theory. Index Terms--Data dropout, data robustness, incomplete in- formation, iterative learning controi（ILC）, quantized control, sampled control, varying lengths.展开更多
Multi-channel sampling for band-limited signals is fundamental in the theory of multi-channel parallel A/D environment and multiplexing wireless communication environment. As the fractional Fourier transform has been ...Multi-channel sampling for band-limited signals is fundamental in the theory of multi-channel parallel A/D environment and multiplexing wireless communication environment. As the fractional Fourier transform has been found wide applications in signal processing fields, it is necessary to consider the multi-channel sampling theorem based on the fractional Fourier transform. In this paper, the multi-channel sampling theorem for the fractional band-limited signal is firstly proposed, which is the generalization of the well-known sampling theorem for the fractional Fourier transform. Since the periodic nonuniformly sampled signal in the fractional Fourier domain has valuable applications, the reconstruction expression for the periodic nonuniformly sampled signal has been then obtained by using the derived multi-channel sampling theorem and the specific space-shifting and phase-shifting properties of the fractional Fourier transform. Moreover, by designing different fractional Fourier filters, we can obtain reconstruction methods for other sampling strategies.展开更多
In this paper,the authors consider the distributed adaptive identification problem over sensor networks using sampled data,where the dynamics of each sensor is described by a stochastic differential equation.By minimi...In this paper,the authors consider the distributed adaptive identification problem over sensor networks using sampled data,where the dynamics of each sensor is described by a stochastic differential equation.By minimizing a local objective function at sampling time instants,the authors propose an online distributed least squares algorithm based on sampled data.A cooperative non-persistent excitation condition is introduced,under which the convergence results of the proposed algorithm are established by properly choosing the sampling time interval.The upper bound on the accumulative regret of the adaptive predictor can also be provided.Finally,the authors demonstrate the cooperative effect of multiple sensors in the estimation of unknown parameters by computer simulations.展开更多
In industrial process control systems,there is overwhelming evidence corroborating the notion that economic or technical limitations result in some key variables that are very difficult to measure online.The data-driv...In industrial process control systems,there is overwhelming evidence corroborating the notion that economic or technical limitations result in some key variables that are very difficult to measure online.The data-driven soft sensor is an effective solution because it provides a reliable and stable online estimation of such variables.This paper employs a deep neural network with multiscale feature extraction layers to build soft sensors,which are applied to the benchmarked Tennessee-Eastman process(TEP)and a real wind farm case.The comparison of modelling results demonstrates that the multiscale feature extraction layers have the following advantages over other methods.First,the multiscale feature extraction layers significantly reduce the number of parameters compared to the other deep neural networks.Second,the multiscale feature extraction layers can powerfully extract dataset characteristics.Finally,the multiscale feature extraction layers with fully considered historical measurements can contain richer useful information and improved representation compared to traditional data-driven models.展开更多
Considering a variety of sampled value(SV)attacks on busbar differential protection(BDP)which poses challenges to conventional learning algorithms,an algorithm to detect SV attacks based on the immune system of negati...Considering a variety of sampled value(SV)attacks on busbar differential protection(BDP)which poses challenges to conventional learning algorithms,an algorithm to detect SV attacks based on the immune system of negative selection is developed in this paper.The healthy SV data of BDP are defined as self-data composed of spheres of the same size,whereas the SV attack data,i.e.,the nonself data,are preserved in the nonself space covered by spherical detectors of different sizes.To avoid the confusion between busbar faults and SV attacks,a self-shape optimization algorithm is introduced,and the improved self-data are verified through a power-frequency fault-component-based differential protection criterion to avoid false negatives.Based on the difficulty of boundary coverage in traditional negative selection algorithms,a self-data-driven detector generation algorithm is proposed to enhance the detector coverage.A testbed of differential protection for a 110 kV double busbar system is then established.Typical SV attacks of BDP such as amplitude and current phase tampering,fault replays,and the disconnection of the secondary circuits of current transformers are considered,and the delays of differential relay operation caused by detection algorithms are investigated.展开更多
Wheat ear counting is a prerequisite for the evaluation of wheat yield.A wheat ear counting method based on frequency domain decomposition is proposed in this study to improve the accuracy of wheat yield estimation.Th...Wheat ear counting is a prerequisite for the evaluation of wheat yield.A wheat ear counting method based on frequency domain decomposition is proposed in this study to improve the accuracy of wheat yield estimation.The frequency domain decomposition of wheat ear image is completed by multiscale support value filter(MSVF)combined with improved sampled contourlet transform(ISCT).Support Vector Machine(SVM)is the classic classification and regression algorithm of machine learning.MSVF based on this has strong frequency domain filtering and generalization ability,which can effectively remove the complex background,while the multi-direction characteristics of ISCT enable it to represent the contour and texture information of wheat ears.In order to improve the level of wheat yield prediction,MSVF-ISCT method is used to decompose the ear image in multiscale and multi direction in frequency domain,reduce the interference of irrelevant information,and generate the sub-band image with more abundant information components of ear feature information.Then,the ear feature is extracted by morphological operation and maximum entropy threshold segmentation,and the skeleton thinning and corner detection algorithms are used to count the results.The number of wheat ears in the image can be accurately counted.Experiments show that compared with the traditional algorithms based on spatial domain,this method significantly improves the accuracy of wheat ear counting,which can provide guidance and application for the field of agricultural precision yield estimation.展开更多
The main aim of this work is to design a non-fragile sampled data control(NFSDC) scheme for the asymptotic synchronization criteria for interconnected coupled circuit systems(multi-agent systems, MASs). NFSDC is used ...The main aim of this work is to design a non-fragile sampled data control(NFSDC) scheme for the asymptotic synchronization criteria for interconnected coupled circuit systems(multi-agent systems, MASs). NFSDC is used to conduct synchronization analysis of the considered MASs in the presence of time-varying delays. By constructing suitable Lyapunov functions, sufficient conditions are derived in terms of linear matrix inequalities(LMIs) to ensure synchronization between the MAS leader and follower systems. Finally, two numerical examples are given to show the effectiveness of the proposed control scheme and less conservation of the proposed Lyapunov functions.展开更多
The practice of integrating images from two or more sensors collected from the same area or object is known as image fusion.The goal is to extract more spatial and spectral information from the resulting fused image t...The practice of integrating images from two or more sensors collected from the same area or object is known as image fusion.The goal is to extract more spatial and spectral information from the resulting fused image than from the component images.The images must be fused to improve the spatial and spectral quality of both panchromatic and multispectral images.This study provides a novel picture fusion technique that employs L0 smoothening Filter,Non-subsampled Contour let Transform(NSCT)and Sparse Representation(SR)followed by the Max absolute rule(MAR).The fusion approach is as follows:first,the multispectral and panchromatic images are divided into lower and higher frequency components using the L0 smoothing filter.Then comes the fusion process,which uses an approach that combines NSCT and SR to fuse low frequency components.Similarly,the Max-absolute fusion rule is used to merge high frequency components.Finally,the final image is obtained through the disintegration of fused low and high frequency data.In terms of correlation coefficient,Entropy,spatial frequency,and fusion mutual information,our method outperforms other methods in terms of image quality enhancement and visual evaluation.展开更多
A chaos control strategy for chaotic current-mode boost converter is presented by using inductor current sampled feedback control technique.The quantitative analysis of control mechanism is performed by establishing a...A chaos control strategy for chaotic current-mode boost converter is presented by using inductor current sampled feedback control technique.The quantitative analysis of control mechanism is performed by establishing a discrete alterative map of the controlled system.The stability criterion,feedback gain,and corresponding critical duty ratio are obtained from the eigenvalue of the map.The simulation results verify the t heoretical analysis results of the control strategy.展开更多
Assessment of tree species diversity, structure and regeneration status of four sacred groves of Kushalnagar,southern Karnataka was carried out. The random quadrat method was employed in each grove for enumeration of ...Assessment of tree species diversity, structure and regeneration status of four sacred groves of Kushalnagar,southern Karnataka was carried out. The random quadrat method was employed in each grove for enumeration of tree diversity and regeneration status. A total of 98 tree species belonging to 38 families were found from the sampled areas.These groves possess higher diversity and basal area. Some67 % of species have shown regeneration, while 17 % of species had no regeneration. Another 15 % of species were reappearing or immigrating. It is observed that increased disturbance was directly proportional to number of reappearing or immigrating species and inversely proportional to the diversity in all the sacred groves. Significant impact on diversity, species richness and regeneration status of the flora due to manifold anthropogenic activities have been recorded.展开更多
This paper deals with the problem of active disturbance rejection control(ADRC)design for a class of uncertain nonlinear systems with sporadic measurements.A novel extended state observer(ESO)is designed in a cascade ...This paper deals with the problem of active disturbance rejection control(ADRC)design for a class of uncertain nonlinear systems with sporadic measurements.A novel extended state observer(ESO)is designed in a cascade form consisting of a continuous time estimator,a continuous observation error predictor,and a reset compensator.The proposed ESO estimates not only the system state but also the total uncertainty,which may include the effects of the external perturbation,the parametric uncertainty,and the unknown nonlinear dynamics.Such a reset compensator,whose state is reset to zero whenever a new measurement arrives,is used to calibrate the predictor.Due to the cascade structure,the resulting error dynamics system is presented in a non-hybrid form,and accordingly,analyzed in a general sampled-data system framework.Based on the output of the ESO,a continuous ADRC law is then developed.The convergence of the resulting closed-loop system is proved under given conditions.Two numerical simulations demonstrate the effectiveness of the proposed control method.展开更多
The network structure of the smart substation in common use was introduced,and the technical problems of the shared-network of sampled measured value(SMV)and generic object oriented substation event(GOOSE)were analyze...The network structure of the smart substation in common use was introduced,and the technical problems of the shared-network of sampled measured value(SMV)and generic object oriented substation event(GOOSE)were analyzed,such as the processing ability of network device and the intelligent device,the data real-time property and the network reliability,the effects to the substation in the condition of network fault,etc.On this basis,the feasibility of the shared-network of SMV and GOOSE was discussed,the implement scheme was presented,and eventually the solution of the shared-network of SMV and GOOSE was put forward,which based on the applications of the message priority control,restricting the switch number,virtual local area network(VLAN)and GARP multicast registration protocol(GMRP)classification flow control,flow rate limiting,etc.In the test-bed,the cases of shared-network and separate-network of SMV and GOOSE were compared and analyzed,and the result was valuable for reference.展开更多
This paper is concerned with the problem of robust H-infinity filtering on uncertain systems under sampled measurements, both continuous disturbance and discrete disturbance are considered in the systems. The paramete...This paper is concerned with the problem of robust H-infinity filtering on uncertain systems under sampled measurements, both continuous disturbance and discrete disturbance are considered in the systems. The parameter uncertainty is assumed to be time-varying norm-bounded. The aim is to design an asymptotically stable filter, using the locally sampled measurements, which ensures both the robust asymptotic stability and a prescribed level of H-infinity performance for the filtering error dynamics for all admissible uncertainties. The derivation process is simplified by introducing auxiliary systems and the sufficient condition for the existence of such a filter is proposed. During the study, the main results were expressed as LMIs by employing various matrix techniques. Using LMI toolbox of Matlab software, it is very convenient to obtain the appropriate filter. Finally, a numerical example shows that the method is effective and feasible.展开更多
The identification of nonlinear systems with multiple sampled rates is a difficult task.The motivation of our paper is to study the parameter estimation problem of Hammerstein systems with dead-zone characteristics by...The identification of nonlinear systems with multiple sampled rates is a difficult task.The motivation of our paper is to study the parameter estimation problem of Hammerstein systems with dead-zone characteristics by using the dual-rate sampled data.Firstly,the auxiliary model identification principle is used to estimate the unmeasurable variables,and the recursive estimation algorithm is proposed to identify the parameters of the static nonlinear model with the dead-zone function and the parameters of the dynamic linear system model.Then,the convergence of the proposed identification algorithm is analyzed by using the martingale convergence theorem.It is proved theoretically that the estimated parameters can converge to the real values under the condition of continuous excitation.Finally,the validity of the proposed algorithm is proved by the identification of the dual-rate sampled nonlinear systems.展开更多
High output powers and wide range tuning have been achieved in a sampled grating distributed Bragg reflector laser with an integrated semiconductor optical amplifier.Tilted amplifier and anti-reflection facet coating ...High output powers and wide range tuning have been achieved in a sampled grating distributed Bragg reflector laser with an integrated semiconductor optical amplifier.Tilted amplifier and anti-reflection facet coating are used to suppress reflection.We have demonstrated sampled grating DBR laser with a tuning range over 38 nm,good wavelength coverage and peak output powers of more than 9 mW for all wavelengths.展开更多
A novel and simple fiber grating sensor based on high-duty-cyclesample fiber bragg grating is proposed and demonstratedexperimentally. This type of sensor can measure strain andtemperature simultaneously with merits o...A novel and simple fiber grating sensor based on high-duty-cyclesample fiber bragg grating is proposed and demonstratedexperimentally. This type of sensor can measure strain andtemperature simultaneously with merits of low cost, high sensitivityand immunity to electro- magnetic interference. The sensor has anaccuracy of 20 με and 0.8 deg.C over a strain range of 500～1 500 με and a temperature range of 5～36 deg.C under experimentalconditions.展开更多
This paper presents a modeling method for a non-uniformly sampled system bused on support vector regression （ SVR ）. First, a lifted discrete-time state-space model for a non-uniformly sampled system is derived by u...This paper presents a modeling method for a non-uniformly sampled system bused on support vector regression （ SVR ）. First, a lifted discrete-time state-space model for a non-uniformly sampled system is derived by using the lifting technique to reduce the modeling difficulty caused by multirate sampling. Then, the system is divided into several parallel subsystems and their input-output model is presented to satisfy the SVR model. Finally, an on-line SVR technique is utilized to establish the models of all subsystems to deal with uncertainty. Furthermore, the presented method is applied in a multichannel electrohydraulic force servo synchronous loading system to predict the system outputs over the control sample interval and the prediction mean absolute percentage error reaches 0. 092%. The results demonstrate that the presented method has a high modeling precision and the subsystems have the same level of prediction error.展开更多
A nonlinear state observer design with sampled and delayed output measurements for variable speed and external load torque estimations of SPMSM drive system has been addressed, successfully. Sampled output state predi...A nonlinear state observer design with sampled and delayed output measurements for variable speed and external load torque estimations of SPMSM drive system has been addressed, successfully. Sampled output state predictor is re-initialized at each sampling instant and remains continuous between two sampling instants. Throughout this study, a positive constant to satisfy an upper limit of the sampling period between sampling instants and allowable timing delay in terms of observer parameters has been prepared such that the exponential stable of the closed-loop system is guaranteed, based on Lyapunov stability tools. In order to validate the theoretical results introduced by main fundamental theorem to prove the observer convergence, the proposed sampled-data observer is demonstrated through a sample study application to variable speed SPMSM drive system.展开更多
On the basis of the coherence theory a new method is presented to analyze the sampled chirped fiber gratings (SCFG). With this method, more results on the SCFG are obtained, including not only the characteristics of r...On the basis of the coherence theory a new method is presented to analyze the sampled chirped fiber gratings (SCFG). With this method, more results on the SCFG are obtained, including not only the characteristics of reflectivity, transmission and time delay, but also the simplified reflectivity formula, the channel's number, wavelength spacing and channel's bandwidth. Therefore, this method is more systematic and perfect than the usual transfer matrix method and can well guide the design of the SCFG.展开更多
基金supported by the National Natural Science Foundation of China(61673045)Beijing Natural Science Foundation(4152040)
文摘Abstract--This paper conducts a survey on iterative learn- ing control （ILC） with incomplete information and associated control system design, which is a frontier of the ILC field. The incomplete information, including passive and active types, can cause data loss or fragment due to various factors. Passive incomplete information refers to incomplete data and information caused by practical system limitations during data collection, storage, transmission, and processing, such as data dropouts, delays, disordering, and limited transmission bandwidth. Active incomplete information refers to incomplete data and information caused by man-made reduction of data quantity and quality on the premise that the given objective is satisfied, such as sampling and quantization. This survey emphasizes two aspects： the first one is how to guarantee good learning performance and tracking performance with passive incomplete data, and the second is how to balance the control performance index and data demand by active means. The promising research directions along this topic are also addressed, where data robustness is highly emphasized. This survey is expected to improve understanding of the restrictive relationship and trade-off between incomplete data and tracking performance, quantitatively, and promote further developments of ILC theory. Index Terms--Data dropout, data robustness, incomplete in- formation, iterative learning controi（ILC）, quantized control, sampled control, varying lengths.
基金Supported partially by the National Natural Science Foundation of China (Grant Nos. 60232010 and 60572094) the National Natural Science Foundation of China for Distinguished Young Scholars (Grant No. 60625104)
文摘Multi-channel sampling for band-limited signals is fundamental in the theory of multi-channel parallel A/D environment and multiplexing wireless communication environment. As the fractional Fourier transform has been found wide applications in signal processing fields, it is necessary to consider the multi-channel sampling theorem based on the fractional Fourier transform. In this paper, the multi-channel sampling theorem for the fractional band-limited signal is firstly proposed, which is the generalization of the well-known sampling theorem for the fractional Fourier transform. Since the periodic nonuniformly sampled signal in the fractional Fourier domain has valuable applications, the reconstruction expression for the periodic nonuniformly sampled signal has been then obtained by using the derived multi-channel sampling theorem and the specific space-shifting and phase-shifting properties of the fractional Fourier transform. Moreover, by designing different fractional Fourier filters, we can obtain reconstruction methods for other sampling strategies.
基金supported by the Natural Science Foundation of China under Grant No.T2293772the National Key R&D Program of China under Grant No.2018YFA0703800+1 种基金the Strategic Priority Research Program of Chinese Academy of Sciences under Grant No.XDA27000000the National Science Foundation of Shandong Province under Grant No.ZR2020ZD26.
文摘In this paper,the authors consider the distributed adaptive identification problem over sensor networks using sampled data,where the dynamics of each sensor is described by a stochastic differential equation.By minimizing a local objective function at sampling time instants,the authors propose an online distributed least squares algorithm based on sampled data.A cooperative non-persistent excitation condition is introduced,under which the convergence results of the proposed algorithm are established by properly choosing the sampling time interval.The upper bound on the accumulative regret of the adaptive predictor can also be provided.Finally,the authors demonstrate the cooperative effect of multiple sensors in the estimation of unknown parameters by computer simulations.
基金supported by National Natural Science Foundation of China(No.61873142)the Science and Technology Research Program of the Chongqing Municipal Education Commission,China(Nos.KJZD-K202201901,KJQN202201109,KJQN202101904,KJQN202001903 and CXQT21035)+2 种基金the Scientific Research Foundation of Chongqing University of Technology,China(No.2019ZD76)the Scientific Research Foundation of Chongqing Institute of Engineering,China(No.2020xzky05)the Chongqing Municipal Natural Science Foundation,China(No.cstc2020jcyj-msxmX0666).
文摘In industrial process control systems,there is overwhelming evidence corroborating the notion that economic or technical limitations result in some key variables that are very difficult to measure online.The data-driven soft sensor is an effective solution because it provides a reliable and stable online estimation of such variables.This paper employs a deep neural network with multiscale feature extraction layers to build soft sensors,which are applied to the benchmarked Tennessee-Eastman process(TEP)and a real wind farm case.The comparison of modelling results demonstrates that the multiscale feature extraction layers have the following advantages over other methods.First,the multiscale feature extraction layers significantly reduce the number of parameters compared to the other deep neural networks.Second,the multiscale feature extraction layers can powerfully extract dataset characteristics.Finally,the multiscale feature extraction layers with fully considered historical measurements can contain richer useful information and improved representation compared to traditional data-driven models.
基金supported by National Natural Science Foundation of China (No.51967003)Guangxi Natural Science Foundation (No.2016GXNSFBA380105)。
文摘Considering a variety of sampled value(SV)attacks on busbar differential protection(BDP)which poses challenges to conventional learning algorithms,an algorithm to detect SV attacks based on the immune system of negative selection is developed in this paper.The healthy SV data of BDP are defined as self-data composed of spheres of the same size,whereas the SV attack data,i.e.,the nonself data,are preserved in the nonself space covered by spherical detectors of different sizes.To avoid the confusion between busbar faults and SV attacks,a self-shape optimization algorithm is introduced,and the improved self-data are verified through a power-frequency fault-component-based differential protection criterion to avoid false negatives.Based on the difficulty of boundary coverage in traditional negative selection algorithms,a self-data-driven detector generation algorithm is proposed to enhance the detector coverage.A testbed of differential protection for a 110 kV double busbar system is then established.Typical SV attacks of BDP such as amplitude and current phase tampering,fault replays,and the disconnection of the secondary circuits of current transformers are considered,and the delays of differential relay operation caused by detection algorithms are investigated.
基金National Natural Science Foundation of China(61672032)National Key Research and Development Program of China(2016YFD0800904)+1 种基金Anhui Provincial Science and Technology Project(16030701091)The Open Research Fund of National Engineering Research Center for Agro-Ecological Big Data Analysis&Application,Anhui University(AE2018009).
文摘Wheat ear counting is a prerequisite for the evaluation of wheat yield.A wheat ear counting method based on frequency domain decomposition is proposed in this study to improve the accuracy of wheat yield estimation.The frequency domain decomposition of wheat ear image is completed by multiscale support value filter(MSVF)combined with improved sampled contourlet transform(ISCT).Support Vector Machine(SVM)is the classic classification and regression algorithm of machine learning.MSVF based on this has strong frequency domain filtering and generalization ability,which can effectively remove the complex background,while the multi-direction characteristics of ISCT enable it to represent the contour and texture information of wheat ears.In order to improve the level of wheat yield prediction,MSVF-ISCT method is used to decompose the ear image in multiscale and multi direction in frequency domain,reduce the interference of irrelevant information,and generate the sub-band image with more abundant information components of ear feature information.Then,the ear feature is extracted by morphological operation and maximum entropy threshold segmentation,and the skeleton thinning and corner detection algorithms are used to count the results.The number of wheat ears in the image can be accurately counted.Experiments show that compared with the traditional algorithms based on spatial domain,this method significantly improves the accuracy of wheat ear counting,which can provide guidance and application for the field of agricultural precision yield estimation.
基金Project supported by the National Natural Science Foundation of China(No.62103103)the Natural Science Foundation of Jiangsu Province,China(No.BK20210223)。
文摘The main aim of this work is to design a non-fragile sampled data control(NFSDC) scheme for the asymptotic synchronization criteria for interconnected coupled circuit systems(multi-agent systems, MASs). NFSDC is used to conduct synchronization analysis of the considered MASs in the presence of time-varying delays. By constructing suitable Lyapunov functions, sufficient conditions are derived in terms of linear matrix inequalities(LMIs) to ensure synchronization between the MAS leader and follower systems. Finally, two numerical examples are given to show the effectiveness of the proposed control scheme and less conservation of the proposed Lyapunov functions.
文摘The practice of integrating images from two or more sensors collected from the same area or object is known as image fusion.The goal is to extract more spatial and spectral information from the resulting fused image than from the component images.The images must be fused to improve the spatial and spectral quality of both panchromatic and multispectral images.This study provides a novel picture fusion technique that employs L0 smoothening Filter,Non-subsampled Contour let Transform(NSCT)and Sparse Representation(SR)followed by the Max absolute rule(MAR).The fusion approach is as follows:first,the multispectral and panchromatic images are divided into lower and higher frequency components using the L0 smoothing filter.Then comes the fusion process,which uses an approach that combines NSCT and SR to fuse low frequency components.Similarly,the Max-absolute fusion rule is used to merge high frequency components.Finally,the final image is obtained through the disintegration of fused low and high frequency data.In terms of correlation coefficient,Entropy,spatial frequency,and fusion mutual information,our method outperforms other methods in terms of image quality enhancement and visual evaluation.
文摘A chaos control strategy for chaotic current-mode boost converter is presented by using inductor current sampled feedback control technique.The quantitative analysis of control mechanism is performed by establishing a discrete alterative map of the controlled system.The stability criterion,feedback gain,and corresponding critical duty ratio are obtained from the eigenvalue of the map.The simulation results verify the t heoretical analysis results of the control strategy.
文摘Assessment of tree species diversity, structure and regeneration status of four sacred groves of Kushalnagar,southern Karnataka was carried out. The random quadrat method was employed in each grove for enumeration of tree diversity and regeneration status. A total of 98 tree species belonging to 38 families were found from the sampled areas.These groves possess higher diversity and basal area. Some67 % of species have shown regeneration, while 17 % of species had no regeneration. Another 15 % of species were reappearing or immigrating. It is observed that increased disturbance was directly proportional to number of reappearing or immigrating species and inversely proportional to the diversity in all the sacred groves. Significant impact on diversity, species richness and regeneration status of the flora due to manifold anthropogenic activities have been recorded.
基金supported by the National Natural Science Foundation of China(61833016,61873295).
文摘This paper deals with the problem of active disturbance rejection control(ADRC)design for a class of uncertain nonlinear systems with sporadic measurements.A novel extended state observer(ESO)is designed in a cascade form consisting of a continuous time estimator,a continuous observation error predictor,and a reset compensator.The proposed ESO estimates not only the system state but also the total uncertainty,which may include the effects of the external perturbation,the parametric uncertainty,and the unknown nonlinear dynamics.Such a reset compensator,whose state is reset to zero whenever a new measurement arrives,is used to calibrate the predictor.Due to the cascade structure,the resulting error dynamics system is presented in a non-hybrid form,and accordingly,analyzed in a general sampled-data system framework.Based on the output of the ESO,a continuous ADRC law is then developed.The convergence of the resulting closed-loop system is proved under given conditions.Two numerical simulations demonstrate the effectiveness of the proposed control method.
文摘The network structure of the smart substation in common use was introduced,and the technical problems of the shared-network of sampled measured value(SMV)and generic object oriented substation event(GOOSE)were analyzed,such as the processing ability of network device and the intelligent device,the data real-time property and the network reliability,the effects to the substation in the condition of network fault,etc.On this basis,the feasibility of the shared-network of SMV and GOOSE was discussed,the implement scheme was presented,and eventually the solution of the shared-network of SMV and GOOSE was put forward,which based on the applications of the message priority control,restricting the switch number,virtual local area network(VLAN)and GARP multicast registration protocol(GMRP)classification flow control,flow rate limiting,etc.In the test-bed,the cases of shared-network and separate-network of SMV and GOOSE were compared and analyzed,and the result was valuable for reference.
基金This work was supported by the National Natural Science Foundation of China (No.60274009) and the National Program (863) of High TechnologyDevelopment(No.2004AA412030).
文摘This paper is concerned with the problem of robust H-infinity filtering on uncertain systems under sampled measurements, both continuous disturbance and discrete disturbance are considered in the systems. The parameter uncertainty is assumed to be time-varying norm-bounded. The aim is to design an asymptotically stable filter, using the locally sampled measurements, which ensures both the robust asymptotic stability and a prescribed level of H-infinity performance for the filtering error dynamics for all admissible uncertainties. The derivation process is simplified by introducing auxiliary systems and the sufficient condition for the existence of such a filter is proposed. During the study, the main results were expressed as LMIs by employing various matrix techniques. Using LMI toolbox of Matlab software, it is very convenient to obtain the appropriate filter. Finally, a numerical example shows that the method is effective and feasible.
基金supported by the National Natural Science Foundation of China(61863034)
文摘The identification of nonlinear systems with multiple sampled rates is a difficult task.The motivation of our paper is to study the parameter estimation problem of Hammerstein systems with dead-zone characteristics by using the dual-rate sampled data.Firstly,the auxiliary model identification principle is used to estimate the unmeasurable variables,and the recursive estimation algorithm is proposed to identify the parameters of the static nonlinear model with the dead-zone function and the parameters of the dynamic linear system model.Then,the convergence of the proposed identification algorithm is analyzed by using the martingale convergence theorem.It is proved theoretically that the estimated parameters can converge to the real values under the condition of continuous excitation.Finally,the validity of the proposed algorithm is proved by the identification of the dual-rate sampled nonlinear systems.
基金Project supported by the National High Technology Research and Development Program of China(Nos.2006AA01Z256,2007AA03Z4 19,2007AA03Z417)the State Key Development Program for Basic Research of China(Nos.2006CB604901,2006CB604902)the National Natural Science Foundation of China(Nos.90401025,60736036,60706009,60777021).
文摘High output powers and wide range tuning have been achieved in a sampled grating distributed Bragg reflector laser with an integrated semiconductor optical amplifier.Tilted amplifier and anti-reflection facet coating are used to suppress reflection.We have demonstrated sampled grating DBR laser with a tuning range over 38 nm,good wavelength coverage and peak output powers of more than 9 mW for all wavelengths.
文摘A novel and simple fiber grating sensor based on high-duty-cyclesample fiber bragg grating is proposed and demonstratedexperimentally. This type of sensor can measure strain andtemperature simultaneously with merits of low cost, high sensitivityand immunity to electro- magnetic interference. The sensor has anaccuracy of 20 με and 0.8 deg.C over a strain range of 500～1 500 με and a temperature range of 5～36 deg.C under experimentalconditions.
文摘This paper presents a modeling method for a non-uniformly sampled system bused on support vector regression （ SVR ）. First, a lifted discrete-time state-space model for a non-uniformly sampled system is derived by using the lifting technique to reduce the modeling difficulty caused by multirate sampling. Then, the system is divided into several parallel subsystems and their input-output model is presented to satisfy the SVR model. Finally, an on-line SVR technique is utilized to establish the models of all subsystems to deal with uncertainty. Furthermore, the presented method is applied in a multichannel electrohydraulic force servo synchronous loading system to predict the system outputs over the control sample interval and the prediction mean absolute percentage error reaches 0. 092%. The results demonstrate that the presented method has a high modeling precision and the subsystems have the same level of prediction error.
文摘A nonlinear state observer design with sampled and delayed output measurements for variable speed and external load torque estimations of SPMSM drive system has been addressed, successfully. Sampled output state predictor is re-initialized at each sampling instant and remains continuous between two sampling instants. Throughout this study, a positive constant to satisfy an upper limit of the sampling period between sampling instants and allowable timing delay in terms of observer parameters has been prepared such that the exponential stable of the closed-loop system is guaranteed, based on Lyapunov stability tools. In order to validate the theoretical results introduced by main fundamental theorem to prove the observer convergence, the proposed sampled-data observer is demonstrated through a sample study application to variable speed SPMSM drive system.
文摘On the basis of the coherence theory a new method is presented to analyze the sampled chirped fiber gratings (SCFG). With this method, more results on the SCFG are obtained, including not only the characteristics of reflectivity, transmission and time delay, but also the simplified reflectivity formula, the channel's number, wavelength spacing and channel's bandwidth. Therefore, this method is more systematic and perfect than the usual transfer matrix method and can well guide the design of the SCFG.
