A novel approach to the inverse problem of diffusively coupled map lattices is systematically investigated by utilizing the symbolic vector dynamics. The relationship between the performance of initial condition estim...A novel approach to the inverse problem of diffusively coupled map lattices is systematically investigated by utilizing the symbolic vector dynamics. The relationship between the performance of initial condition estimation and the structural feature of dynamical system is proved theoretically. It is found that any point in a spatiotemporal coupled system is not necessary to converge to its initial value with respect to sufficient backward iteration, which is directly relevant to the coupling strength and local mapping function. When the convergence is met, the error bound in estimating the initial condition is proposed in a noiseless environment, which is determined by the dimension of attractors and metric entropy of the system. Simulation results further confirm the theoretic analysis, and prove that the presented method provides the important theory and experimental results for better analysing and characterizing the spatiotemporal complex behaviours in an actual system.展开更多
Based on symbolic dynamics, a novel computationally efficient algorithm is proposed to estimate the unknown initial vectors of globally coupled map lattices （CMLs）. It is proved that not all inverse chaotic mapping ...Based on symbolic dynamics, a novel computationally efficient algorithm is proposed to estimate the unknown initial vectors of globally coupled map lattices （CMLs）. It is proved that not all inverse chaotic mapping functions are satisfied for contraction mapping. It is found that the values in phase space do not always converge on their initial values with respect to sufficient backward iteration of the symbolic vectors in terms of global convergence or divergence （CD）. Both CD property and the coupling strength are directly related to the mapping function of the existing CML. Furthermore, the CD properties of Logistic, Bernoulli, and Tent chaotic mapping functions are investigated and compared. Various simulation results and the performances of the initial vector estimation with different signal-to- noise ratios （SNRs） are also provided to confirm the proposed algorithm. Finally, based on the spatiotemporal chaotic characteristics of the CML, the conditions of estimating the initial vectors usiug symbolic dynamics are discussed. The presented method provides both theoretical and experimental results for better understanding and characterizing the behaviours of spatiotemporal chaotic systems.展开更多
A novel computationally efficient algorithm in terms of the time-varying symbolic dynamic method is proposed to estimate the unknown initial conditions of coupled map lattices （CMLs）. The presented method combines s...A novel computationally efficient algorithm in terms of the time-varying symbolic dynamic method is proposed to estimate the unknown initial conditions of coupled map lattices （CMLs）. The presented method combines symbolic dynamics with time-varying control parameters to develop a time-varying scheme for estimating the initial condition of multi-dimensional spatiotemporal chaotic signals. The performances of the presented time-varying estimator in both noiseless and noisy environments are analysed and compared with the common time-invariant estimator. Simulations are carried out and the obtained results show that the proposed method provides an efficient estimation of the initial condition of each lattice in the coupled system. The algorithm cannot yield an asymptotically unbiased estimation due to the effect of the coupling term, but the estimation with the time-varying algorithm is closer to the Cramer-Rao lower bound （CRLB） than that with the time-invariant estimation method, especially at high signal-to-noise ratios （SNRs）.展开更多
A novel nonlinear model for surface permanent magnet synchronous motors（SPMSMs） is adopted to estimate the initial rotor position for hybrid electric vehicles（HEVs）. Usually, the accuracy of initial rotor position...A novel nonlinear model for surface permanent magnet synchronous motors（SPMSMs） is adopted to estimate the initial rotor position for hybrid electric vehicles（HEVs）. Usually, the accuracy of initial rotor position estimation for SPMSMs relies on magnetic saturation. To verify the saturation effect, the transient finite element analysis（FEA） model is presented first. Hybrid injection of a static voltage vector（SVV） superimposed with a high-frequency rotating voltage is proposed. The magnetic polarity is roughly identified with the aid of the saturation evaluation function, based on which an estimation of the position is performed. During this procedure, a special demodulation is suggested to extract signals of iron core saturation and rotor position. A Simulink/MATLAB platform for SPMSMs at standstill is constituted, and the effectiveness of the proposed strategy is verified. The proposed method is also validated by experimental results of an SPMSM drive.展开更多
Sensor-fusion based navigation attracts significant attentions for its robustness and accuracy in various applications. To achieve a versatile and efficient state estimation both indoor and outdoor, this paper present...Sensor-fusion based navigation attracts significant attentions for its robustness and accuracy in various applications. To achieve a versatile and efficient state estimation both indoor and outdoor, this paper presents an improved monocular visual inertial navigation architecture within the Multi-State Constraint Kalman Filter （MSCKF）. In addition, to alleviate the initialization demands by appending enough stable poses in MSCKF, a rapid and robust Initialization MSCKF （I-MSCKF） navigation method is proposed in the paper. Based on the trifocal tensor and sigmapoint filter, the initialization of the integrated navigation can be accomplished within three consecutive visual frames. Thus, the proposed I-MSCKF method can improve the navigation performance when suffered from shocks at the initial stage. Moreover, the sigma-point filter is applied at initial stage to improve the accuracy for state estimation. The state vector generated at initial stage from the proposed method is consistent with MSCKF, and thus a seamless transition can be achieved between the initialization and the subsequent navigation in I-MSCKF. Finally, the experimental results show that the proposed I-MSCKF method can improve the robustness and accuracy for monocular visual inertial navigations.展开更多
The sequential method is easy to integrate with existing large-scale alternating current(AC)power flow solvers and is therefore a common approach for solving the power flow of AC/direct current(DC)hybrid systems.In th...The sequential method is easy to integrate with existing large-scale alternating current(AC)power flow solvers and is therefore a common approach for solving the power flow of AC/direct current(DC)hybrid systems.In this paper,a highperformance graph computing based distributed parallel implementation of the sequential method with an improved initial estimate approach for hybrid AC/DC systems is developed.The proposed approach is capable of speeding up the entire computation process without compromising the accuracy of result.First,the AC/DC network is intuitively represented by a graph and stored in a graph database(GDB)to expedite data processing.Considering the interconnection of AC grids via high-voltage direct current(HVDC)links,the network is subsequently partitioned into independent areas which are naturally fit for distributed power flow analysis.For each area,the fast-decoupled power flow(FDPF)is employed with node-based parallel computing(NPC)and hierarchical parallel computing(HPC)to quickly identify system states.Furthermore,to reduce the alternate iterations in the sequential method,a new decoupled approach is utilized to achieve a good initial estimate for the Newton-Raphson method.With the improved initial estimate,the sequential method can converge in fewer iterations.Consequently,the proposed approach allows for significant reduction in computing time and is able to meet the requirement of the real-time analysis platform for power system.The performance is verified on standard IEEE 300-bus system,extended large-scale systems,and a practical 11119-bus system in China.展开更多
Aiming at the disadvantages of the traditional projection onto convex sets of blurry edges and lack of image details,this paper proposes an improved projection onto convex sets（POCS） method to enhance the quality of...Aiming at the disadvantages of the traditional projection onto convex sets of blurry edges and lack of image details,this paper proposes an improved projection onto convex sets（POCS） method to enhance the quality of image super-resolution reconstruction（SRR）.In traditional POCS method,bilinear interpolation easily blurs the image.In order to improve the initial estimation of high-resolution image（HRI） during reconstruction of POCS algorithm,the initial estimation of HRI is obtained through iterative curvature-based interpolation（ICBI） instead of bilinear interpolation.Compared with the traditional POCS algorithm,the experimental results in subjective evaluation and objective evaluation demonstrate the effectiveness of the proposed method.The visual effect is improved significantly and image detail information is preserved better.展开更多
基金Project supported by the National Natural Science Foundation of China (Grant Nos. 60571066,60271023 and 61072037)the Natural Science Foundation of Guangdong Province,China (Grant No. 07008126)
文摘A novel approach to the inverse problem of diffusively coupled map lattices is systematically investigated by utilizing the symbolic vector dynamics. The relationship between the performance of initial condition estimation and the structural feature of dynamical system is proved theoretically. It is found that any point in a spatiotemporal coupled system is not necessary to converge to its initial value with respect to sufficient backward iteration, which is directly relevant to the coupling strength and local mapping function. When the convergence is met, the error bound in estimating the initial condition is proposed in a noiseless environment, which is determined by the dimension of attractors and metric entropy of the system. Simulation results further confirm the theoretic analysis, and prove that the presented method provides the important theory and experimental results for better analysing and characterizing the spatiotemporal complex behaviours in an actual system.
基金Project supported by the National Natural Science Foundation of China (Grant Nos. 61072037 and 60271023)the Natural Science Foundation of Guangdong Province,China (Grant No. 10151503101000011)
文摘Based on symbolic dynamics, a novel computationally efficient algorithm is proposed to estimate the unknown initial vectors of globally coupled map lattices （CMLs）. It is proved that not all inverse chaotic mapping functions are satisfied for contraction mapping. It is found that the values in phase space do not always converge on their initial values with respect to sufficient backward iteration of the symbolic vectors in terms of global convergence or divergence （CD）. Both CD property and the coupling strength are directly related to the mapping function of the existing CML. Furthermore, the CD properties of Logistic, Bernoulli, and Tent chaotic mapping functions are investigated and compared. Various simulation results and the performances of the initial vector estimation with different signal-to- noise ratios （SNRs） are also provided to confirm the proposed algorithm. Finally, based on the spatiotemporal chaotic characteristics of the CML, the conditions of estimating the initial vectors usiug symbolic dynamics are discussed. The presented method provides both theoretical and experimental results for better understanding and characterizing the behaviours of spatiotemporal chaotic systems.
基金supported by the National Natural Science Foundation of China(Grant Nos 60271023 and 60571066)the Natural Science Foundation of Guangdong Province,China(Grant Nos 5008317 and 7118382)
文摘A novel computationally efficient algorithm in terms of the time-varying symbolic dynamic method is proposed to estimate the unknown initial conditions of coupled map lattices （CMLs）. The presented method combines symbolic dynamics with time-varying control parameters to develop a time-varying scheme for estimating the initial condition of multi-dimensional spatiotemporal chaotic signals. The performances of the presented time-varying estimator in both noiseless and noisy environments are analysed and compared with the common time-invariant estimator. Simulations are carried out and the obtained results show that the proposed method provides an efficient estimation of the initial condition of each lattice in the coupled system. The algorithm cannot yield an asymptotically unbiased estimation due to the effect of the coupling term, but the estimation with the time-varying algorithm is closer to the Cramer-Rao lower bound （CRLB） than that with the time-invariant estimation method, especially at high signal-to-noise ratios （SNRs）.
基金Project supported by the National Natural Science Foundation of China（Nos.51207029 and 51507039） the Fundamental Research Funds for the Central Universities,China（No.HIT.NSRIF.2017013） the China Postdoctoral Science Foundation（No.2016M591529）
文摘A novel nonlinear model for surface permanent magnet synchronous motors（SPMSMs） is adopted to estimate the initial rotor position for hybrid electric vehicles（HEVs）. Usually, the accuracy of initial rotor position estimation for SPMSMs relies on magnetic saturation. To verify the saturation effect, the transient finite element analysis（FEA） model is presented first. Hybrid injection of a static voltage vector（SVV） superimposed with a high-frequency rotating voltage is proposed. The magnetic polarity is roughly identified with the aid of the saturation evaluation function, based on which an estimation of the position is performed. During this procedure, a special demodulation is suggested to extract signals of iron core saturation and rotor position. A Simulink/MATLAB platform for SPMSMs at standstill is constituted, and the effectiveness of the proposed strategy is verified. The proposed method is also validated by experimental results of an SPMSM drive.
基金the supports of the Beijing Key Laboratory of Digital Design&Manufacturethe Academic Excellence Foundation of Beihang University for Ph.D.Studentsthe MIIT(Ministry of Industry and Information Technology)Key Laboratory of Smart Manufacturing for High-end Aerospace Products
文摘Sensor-fusion based navigation attracts significant attentions for its robustness and accuracy in various applications. To achieve a versatile and efficient state estimation both indoor and outdoor, this paper presents an improved monocular visual inertial navigation architecture within the Multi-State Constraint Kalman Filter （MSCKF）. In addition, to alleviate the initialization demands by appending enough stable poses in MSCKF, a rapid and robust Initialization MSCKF （I-MSCKF） navigation method is proposed in the paper. Based on the trifocal tensor and sigmapoint filter, the initialization of the integrated navigation can be accomplished within three consecutive visual frames. Thus, the proposed I-MSCKF method can improve the navigation performance when suffered from shocks at the initial stage. Moreover, the sigma-point filter is applied at initial stage to improve the accuracy for state estimation. The state vector generated at initial stage from the proposed method is consistent with MSCKF, and thus a seamless transition can be achieved between the initialization and the subsequent navigation in I-MSCKF. Finally, the experimental results show that the proposed I-MSCKF method can improve the robustness and accuracy for monocular visual inertial navigations.
基金supported by the State Grid Corporation Technology Project(No.5455HJ180022)。
文摘The sequential method is easy to integrate with existing large-scale alternating current(AC)power flow solvers and is therefore a common approach for solving the power flow of AC/direct current(DC)hybrid systems.In this paper,a highperformance graph computing based distributed parallel implementation of the sequential method with an improved initial estimate approach for hybrid AC/DC systems is developed.The proposed approach is capable of speeding up the entire computation process without compromising the accuracy of result.First,the AC/DC network is intuitively represented by a graph and stored in a graph database(GDB)to expedite data processing.Considering the interconnection of AC grids via high-voltage direct current(HVDC)links,the network is subsequently partitioned into independent areas which are naturally fit for distributed power flow analysis.For each area,the fast-decoupled power flow(FDPF)is employed with node-based parallel computing(NPC)and hierarchical parallel computing(HPC)to quickly identify system states.Furthermore,to reduce the alternate iterations in the sequential method,a new decoupled approach is utilized to achieve a good initial estimate for the Newton-Raphson method.With the improved initial estimate,the sequential method can converge in fewer iterations.Consequently,the proposed approach allows for significant reduction in computing time and is able to meet the requirement of the real-time analysis platform for power system.The performance is verified on standard IEEE 300-bus system,extended large-scale systems,and a practical 11119-bus system in China.
基金Project supported by the National Natural Science Foundation of China(Nos.61275099,61671094)the Natural Science Foundation of Chongqing Science and Technology Commission(No.CSTC2015JCYJA40032)
文摘Aiming at the disadvantages of the traditional projection onto convex sets of blurry edges and lack of image details,this paper proposes an improved projection onto convex sets（POCS） method to enhance the quality of image super-resolution reconstruction（SRR）.In traditional POCS method,bilinear interpolation easily blurs the image.In order to improve the initial estimation of high-resolution image（HRI） during reconstruction of POCS algorithm,the initial estimation of HRI is obtained through iterative curvature-based interpolation（ICBI） instead of bilinear interpolation.Compared with the traditional POCS algorithm,the experimental results in subjective evaluation and objective evaluation demonstrate the effectiveness of the proposed method.The visual effect is improved significantly and image detail information is preserved better.
