In this study,the state estimation problems for linear discrete systems with uncertain parameters,deterministic input signals and d-step measurement delay are investigated.A robust state estimator with a similar itera...In this study,the state estimation problems for linear discrete systems with uncertain parameters,deterministic input signals and d-step measurement delay are investigated.A robust state estimator with a similar iterative form and comparable computational complexity to the Kalman filter is derived based on the state augmentation method and the sensitivity penalisation of the innovation process.It is discussed that the steady-state properties such as boundedness and convergence of the robust state estimator under the assumptions that the system parameters are time invariant.Numerical simulation results show that compared with the Kalman filter,the obtained state estimator is more robust to modelling errors and has nice estimation accuracy.展开更多
Special input signals identification method based on the auxiliary model based multi-innovation stochastic gradient algorithm for Hammerstein output-error system was proposed.The special input signals were used to rea...Special input signals identification method based on the auxiliary model based multi-innovation stochastic gradient algorithm for Hammerstein output-error system was proposed.The special input signals were used to realize the identification and separation of the Hammerstein model.As a result,the identification of the dynamic linear part can be separated from the static nonlinear elements without any redundant adjustable parameters.The auxiliary model based multi-innovation stochastic gradient algorithm was applied to identifying the serial link parameters of the Hammerstein model.The auxiliary model based multi-innovation stochastic gradient algorithm can avoid the influence of noise and improve the identification accuracy by changing the innovation length.The simulation results show the efficiency of the proposed method.展开更多
Using the linear approximation method, we study a single-mode laser system driven by colored pump noise and quantum noise with coupling between the real and imaginary parts when the laser is operated well above thresh...Using the linear approximation method, we study a single-mode laser system driven by colored pump noise and quantum noise with coupling between the real and imaginary parts when the laser is operated well above threshold. The steady state mean intensity fluctuation C(0) and signal-to-noise ratio (SNR) are calculated. It is found that there is a maximum in SNR when there is a minimum in the fluctuation of laser system if the coupling coefficient between real and imaginary parts of the quantum noise equals zero.展开更多
基金supported by National Natural Science Foundation of China,Grant Number:61873138Shandong Provincial Natural Science Foundation,Grant Number:ZR2019MF063,ZR2020MF064.
文摘In this study,the state estimation problems for linear discrete systems with uncertain parameters,deterministic input signals and d-step measurement delay are investigated.A robust state estimator with a similar iterative form and comparable computational complexity to the Kalman filter is derived based on the state augmentation method and the sensitivity penalisation of the innovation process.It is discussed that the steady-state properties such as boundedness and convergence of the robust state estimator under the assumptions that the system parameters are time invariant.Numerical simulation results show that compared with the Kalman filter,the obtained state estimator is more robust to modelling errors and has nice estimation accuracy.
基金National Natural Science Foundation of China(No.61374044)Shanghai Science Technology Commission,China(Nos.15510722100,16111106300)
文摘Special input signals identification method based on the auxiliary model based multi-innovation stochastic gradient algorithm for Hammerstein output-error system was proposed.The special input signals were used to realize the identification and separation of the Hammerstein model.As a result,the identification of the dynamic linear part can be separated from the static nonlinear elements without any redundant adjustable parameters.The auxiliary model based multi-innovation stochastic gradient algorithm was applied to identifying the serial link parameters of the Hammerstein model.The auxiliary model based multi-innovation stochastic gradient algorithm can avoid the influence of noise and improve the identification accuracy by changing the innovation length.The simulation results show the efficiency of the proposed method.
基金This work was supported by the National Natural Science Foundation of China (No. 10275025)Emphases Item of Education Office of Hubei Province, China (No. 2003A001).
文摘Using the linear approximation method, we study a single-mode laser system driven by colored pump noise and quantum noise with coupling between the real and imaginary parts when the laser is operated well above threshold. The steady state mean intensity fluctuation C(0) and signal-to-noise ratio (SNR) are calculated. It is found that there is a maximum in SNR when there is a minimum in the fluctuation of laser system if the coupling coefficient between real and imaginary parts of the quantum noise equals zero.
