为了充分利用不同类型的时间传递链路,需要实现不同采样率下时间传递链路数据的融合应用,提出了一种基于多分辨率分析的数据融合方法.首先对原始数据进行小波分解,把数据分解到统一的分辨率,初步消除高频噪声;然后在不同分辨率下进行Kal...为了充分利用不同类型的时间传递链路,需要实现不同采样率下时间传递链路数据的融合应用,提出了一种基于多分辨率分析的数据融合方法.首先对原始数据进行小波分解,把数据分解到统一的分辨率,初步消除高频噪声;然后在不同分辨率下进行Kalman滤波;最后通过Mallat快速重构算法得到融合结果.使用该方法处理中国科学院国家授时中心(National Time Service Center,NTSC)和德国联邦物理技术研究所(PhysikalischTechnische Bundesanstalt,PTB)之间的时间传递数据,结果显示融合算法能够处理链路异常或中断造成的数据问题.由于GPS(Global Positioning System)PPP(Precise Point Positioning solutions)链路实测结果性能整体优于TWSTFT(Two-Way Satellite Time and Frequency Transfer)链路,因此用GPS PPP链路测量结果评估融合算法增益.以快速协调世界时(Rapid Realization of Coordinated Universal Time,UTCr)为参考,数据融合结果的准确性增益约1%,日频率稳定度增益优于20%.同时融合算法可以抑制TWSTFT链路的周期噪声,能够有效提高链路的稳定性和鲁棒性.展开更多
A novel discrete-time reaching law was proposed for uncertain discrete-time system,which contained process noise and measurement noise.The proposed method reserves all the advantages of discrete-time reaching law,whic...A novel discrete-time reaching law was proposed for uncertain discrete-time system,which contained process noise and measurement noise.The proposed method reserves all the advantages of discrete-time reaching law,which not only decreases the band width of sliding mode and strengthens the system robustness,but also improves the dynamic performance and stability capability of the system.Moreover,a discrete-time sliding mode control strategy based on Kalman filter method was designed,and Kalman filter was employed to eliminate the influence of system noise.Simulation results show that there is no chattering phenomenon in the output of controller and the state variables of controlled system,and the proposed algorithm is also feasible and has strong robustness to external disturbances.展开更多
This work presents an integrated pressure-tracking controller for a novel electro-hydraulic brake(EHB) system considering friction and hydraulic disturbances. To this end, a mathematical model of an EHB system, consis...This work presents an integrated pressure-tracking controller for a novel electro-hydraulic brake(EHB) system considering friction and hydraulic disturbances. To this end, a mathematical model of an EHB system, consisting of actuator and hydraulic sub-systems, is derived for describing the fundamental dynamics of the system and designing the controller. Due to sensor inaccuracy and measurement noise, a Kalman filter is constructed to estimate push rod stroke for generating desired master cylinder pressure. To improve pressure-tracking accuracy, a linear friction model is generated by linearizing the nonlinear Tustin friction model, and the unmodeled friction disturbances are assumed unknown but bounded. A sliding mode controller is designed for compensating friction disturbances, and the stability of the controller is investigated using the Lyapunov method. The performance of the proposed integrated controller is evaluated with a hardware-in-the-loop(HIL) test platform equipped with the EHB prototype. The test results demonstrate that the EHB system with the proposed integrated controller not only achieves good pressure-tracking performance, but also maintains robustness to friction disturbances.展开更多
Pure inertial navigation system(INS) has divergent localization errors after a long time. In order to compensate the disadvantage, wireless sensor network(WSN) associated with the INS was applied to estimate the mobil...Pure inertial navigation system(INS) has divergent localization errors after a long time. In order to compensate the disadvantage, wireless sensor network(WSN) associated with the INS was applied to estimate the mobile target positioning. Taking traditional Kalman filter(KF) as the framework, the system equation of KF was established by the INS and the observation equation of position errors was built by the WSN. Meanwhile, the observation equation of velocity errors was established by the velocity difference between the INS and WSN, then the covariance matrix of Kalman filter measurement noise was adjusted with fuzzy inference system(FIS), and the fuzzy adaptive Kalman filter(FAKF) based on the INS/WSN was proposed. The simulation results show that the FAKF method has better accuracy and robustness than KF and EKF methods and shows good adaptive capacity with time-varying system noise. Finally, experimental results further prove that FAKF has the fast convergence error, in comparison with KF and EKF methods.展开更多
文摘为了充分利用不同类型的时间传递链路,需要实现不同采样率下时间传递链路数据的融合应用,提出了一种基于多分辨率分析的数据融合方法.首先对原始数据进行小波分解,把数据分解到统一的分辨率,初步消除高频噪声;然后在不同分辨率下进行Kalman滤波;最后通过Mallat快速重构算法得到融合结果.使用该方法处理中国科学院国家授时中心(National Time Service Center,NTSC)和德国联邦物理技术研究所(PhysikalischTechnische Bundesanstalt,PTB)之间的时间传递数据,结果显示融合算法能够处理链路异常或中断造成的数据问题.由于GPS(Global Positioning System)PPP(Precise Point Positioning solutions)链路实测结果性能整体优于TWSTFT(Two-Way Satellite Time and Frequency Transfer)链路,因此用GPS PPP链路测量结果评估融合算法增益.以快速协调世界时(Rapid Realization of Coordinated Universal Time,UTCr)为参考,数据融合结果的准确性增益约1%,日频率稳定度增益优于20%.同时融合算法可以抑制TWSTFT链路的周期噪声,能够有效提高链路的稳定性和鲁棒性.
基金Project(50721063) supported by the National Natural Science Foundation of China
文摘A novel discrete-time reaching law was proposed for uncertain discrete-time system,which contained process noise and measurement noise.The proposed method reserves all the advantages of discrete-time reaching law,which not only decreases the band width of sliding mode and strengthens the system robustness,but also improves the dynamic performance and stability capability of the system.Moreover,a discrete-time sliding mode control strategy based on Kalman filter method was designed,and Kalman filter was employed to eliminate the influence of system noise.Simulation results show that there is no chattering phenomenon in the output of controller and the state variables of controlled system,and the proposed algorithm is also feasible and has strong robustness to external disturbances.
基金Projects(51405008,51175015)supported by the National Natural Science Foundation of ChinaProject(2012AA110904)supported by the National High Technology Research and Development Program of China
文摘This work presents an integrated pressure-tracking controller for a novel electro-hydraulic brake(EHB) system considering friction and hydraulic disturbances. To this end, a mathematical model of an EHB system, consisting of actuator and hydraulic sub-systems, is derived for describing the fundamental dynamics of the system and designing the controller. Due to sensor inaccuracy and measurement noise, a Kalman filter is constructed to estimate push rod stroke for generating desired master cylinder pressure. To improve pressure-tracking accuracy, a linear friction model is generated by linearizing the nonlinear Tustin friction model, and the unmodeled friction disturbances are assumed unknown but bounded. A sliding mode controller is designed for compensating friction disturbances, and the stability of the controller is investigated using the Lyapunov method. The performance of the proposed integrated controller is evaluated with a hardware-in-the-loop(HIL) test platform equipped with the EHB prototype. The test results demonstrate that the EHB system with the proposed integrated controller not only achieves good pressure-tracking performance, but also maintains robustness to friction disturbances.
基金Project(2013AA06A411)supported by the National High Technology Research and Development Program of ChinaProject(CXZZ14_1374)supported by the Graduate Education Innovation Program of Jiangsu Province,ChinaProject supported by the Priority Academic Program Development of Jiangsu Higher Education Institutions,China
文摘Pure inertial navigation system(INS) has divergent localization errors after a long time. In order to compensate the disadvantage, wireless sensor network(WSN) associated with the INS was applied to estimate the mobile target positioning. Taking traditional Kalman filter(KF) as the framework, the system equation of KF was established by the INS and the observation equation of position errors was built by the WSN. Meanwhile, the observation equation of velocity errors was established by the velocity difference between the INS and WSN, then the covariance matrix of Kalman filter measurement noise was adjusted with fuzzy inference system(FIS), and the fuzzy adaptive Kalman filter(FAKF) based on the INS/WSN was proposed. The simulation results show that the FAKF method has better accuracy and robustness than KF and EKF methods and shows good adaptive capacity with time-varying system noise. Finally, experimental results further prove that FAKF has the fast convergence error, in comparison with KF and EKF methods.
