为了准确地辨识电力系统低频振荡模态参数,该文提出了基于数学形态学MM(mathematical morphol-ogy)和总体最小二乘法的旋转不变技术TLS-ESPRIT(total least squares-estimation of signal parameters viarotational invariance techniq...为了准确地辨识电力系统低频振荡模态参数,该文提出了基于数学形态学MM(mathematical morphol-ogy)和总体最小二乘法的旋转不变技术TLS-ESPRIT(total least squares-estimation of signal parameters viarotational invariance technique)的电力系统低频振荡模态参数识别新方法。首先运用基于数学形态学原理而构成形态滤波器对含有噪声的电力系统低频振荡测量信号进行滤波和平稳化处理,去除噪声,提高辨识精度;然后由TLS-ESPRIT算法辨识出电力系统低频振荡模态参数,该算法把信号分成信号子空间和噪声子空间,能够得到更符合电力系统实际的降阶模型和主导模态,有助于电力系统振荡特性分析和阻尼控制器的设计研究。数值仿真分析表明该方法的可行性和有效性。展开更多
The globally optimal recursive filtering problem is studied for a class of systems with random parameter matrices,stochastic nonlinearities, correlated noises and missing measurements. The stochastic nonlinearities ar...The globally optimal recursive filtering problem is studied for a class of systems with random parameter matrices,stochastic nonlinearities, correlated noises and missing measurements. The stochastic nonlinearities are presented in the system model to reflect multiplicative random disturbances, and the additive noises, process noise and measurement noise, are assumed to be one-step autocorrelated as well as two-step cross-correlated.A series of random variables is introduced as the missing rates governing the intermittent measurement losses caused by unfavorable network conditions. The aim of the addressed filtering problem is to design an optimal recursive filter for the uncertain systems based on an innovation approach such that the filtering error is globally minimized at each sampling time. A numerical simulation example is provided to illustrate the effectiveness and applicability of the proposed algorithm.展开更多
The paper firstly defined the remote sensing information quantification, analyzed the necessity of developing remote sensing quantification, figured out the application guidelines requirement, and pointed out the impo...The paper firstly defined the remote sensing information quantification, analyzed the necessity of developing remote sensing quantification, figured out the application guidelines requirement, and pointed out the importance of quantification research. Then taking the remote sensing application research of CBERS-02 data quantification as the example, the paper described the whole quantification system of “remotely sensed digital signal-radiation information-field parameter inversion”. Finally the paper gave the prospect for the development trend of the quantitative remote sensing.展开更多
文摘为了准确地辨识电力系统低频振荡模态参数,该文提出了基于数学形态学MM(mathematical morphol-ogy)和总体最小二乘法的旋转不变技术TLS-ESPRIT(total least squares-estimation of signal parameters viarotational invariance technique)的电力系统低频振荡模态参数识别新方法。首先运用基于数学形态学原理而构成形态滤波器对含有噪声的电力系统低频振荡测量信号进行滤波和平稳化处理,去除噪声,提高辨识精度;然后由TLS-ESPRIT算法辨识出电力系统低频振荡模态参数,该算法把信号分成信号子空间和噪声子空间,能够得到更符合电力系统实际的降阶模型和主导模态,有助于电力系统振荡特性分析和阻尼控制器的设计研究。数值仿真分析表明该方法的可行性和有效性。
基金supported by the National Natural Science Foundation of China(61233005)the National Basic Research Program of China(973 Program)(2014CB744200)
文摘The globally optimal recursive filtering problem is studied for a class of systems with random parameter matrices,stochastic nonlinearities, correlated noises and missing measurements. The stochastic nonlinearities are presented in the system model to reflect multiplicative random disturbances, and the additive noises, process noise and measurement noise, are assumed to be one-step autocorrelated as well as two-step cross-correlated.A series of random variables is introduced as the missing rates governing the intermittent measurement losses caused by unfavorable network conditions. The aim of the addressed filtering problem is to design an optimal recursive filter for the uncertain systems based on an innovation approach such that the filtering error is globally minimized at each sampling time. A numerical simulation example is provided to illustrate the effectiveness and applicability of the proposed algorithm.
文摘The paper firstly defined the remote sensing information quantification, analyzed the necessity of developing remote sensing quantification, figured out the application guidelines requirement, and pointed out the importance of quantification research. Then taking the remote sensing application research of CBERS-02 data quantification as the example, the paper described the whole quantification system of “remotely sensed digital signal-radiation information-field parameter inversion”. Finally the paper gave the prospect for the development trend of the quantitative remote sensing.
