A method for computing the gain matrix is given based on the modal coordinate equation.
在广义模态坐标的基础上讨论了增益矩阵的计算方法。
With introduction of fictitious output, the solution of output feedback gain matrix is simplified.
通过引入假象输出，简化了反馈增益阵的术解过程。
The optimal feedback gain matrix can be obtained by solving a static output feedback controller problem.
通过求解利用降维状态观测器的静态输出反馈，可得到降阶控制的最优反馈增益阵。
The gain matrix of the condition monitor is determined according to the conditions of convergence of the monitor.
根据观测器收敛条件确定状态观测器增益矩阵。
Optimal controller is combined of a optimal reduced order state estimator and a optimal static output feedback gain matrix.
动态反馈控制器可表示为一个最优降维状态估值器和一个最优静态反馈增益阵。
Based on separation theory for descriptor systems, control systems can tolerate sensor failure by adjusting the parameters of observer gain matrix.
根据广义系统的分离定理，当传感器失效，利用调整观测器增益阵参数的办法来实现容错。
On the other hand, by prefixing some elements in the output feedback gain matrix, the casual condition of the controller is automatically satisfied.
同时通过预先固定反馈增益阵中的某些元素的方法，使得控制器满足因果约束的要求。
The constraints due to the decentralized control structure and the casual condition have posed structure constraints on the output feedback gain matrix.
由于分散控制的结构和因果约束的要求，给输出反馈矩阵加上了结构上的约束。
The method sets system disturbance within the feedback gain matrix f, which can be computed by iteration, in order to make the closed loop system optimum.
该方法设定外部干扰矩阵，基于全状态的分散，将系统干扰项考虑到反馈增益矩阵f中，用迭代方法求F阵以使闭环系统最优。
A power control algorithm for the downlink of a distributed antenna wireless communication system is proposed by the use of the average channel gain matrix.
提出了一种基于平均信道增益矩阵的分布式天线无线通信系统下行功率控制算法。
Gain matrix K is a constant matrix design at sea-level static condition, and should be transformed to actual flight condition with similarity correction factors.
增益矩阵在标准大气条件下设计，并通过相似理论将其扩展到全线。
The main merit of the method is that the process can be carried out without knowing the gain matrix first and at the same time the gain matrix can also be determined.
该方法的主要优点是判定过程不必事先知道观测器增益矩阵，判断成功的同时即可定出增益矩阵。
Based on real-time estimation of noise matrix and grey clustering of state variable, filter or gain matrix is modulated so as to get an estimation of the state vector.
实时估计出系统噪声方差矩阵和量测噪声方差矩阵，对状态变量进行灰色聚类，并对滤波矩阵和增益矩阵进行实时自适应调整，计算出状态向量的递推估计值。
At meanwhile, it can be seen that different state gain matrix can be gotten by applying different solution method for a certain question of pole-placement of state feedback.
对于一个确定的状态反馈极点配置问题，当采用不同的方法去求解时，可以得到不同的状态增益阵。
Based on the model, the Taylor series coefficients of control function are adjusted by an iterative learning law and the learning gain matrix is designed via LMI optimization.
模型的基础上，泰勒级数的系数调整控制功能的迭代学习法律，学习增益矩阵，通过LMI优化设计。
This method estimates filter gain matrix K directly, avoids calculating system noise covariance matrix Q and measure noise covariance matrix r, it improves stability of the system.
这种方法采用直接估计增益K，避免了求解系统噪声方差阵q和量测噪声方差阵r，使系统的稳定性增强。
The correlations between measurement noises and processing noises are added to the gain matrix of tracking filter, so information that can describe multi-sensors fusion systems is increased.
在跟踪滤波器的增益阵中引入测量噪声与过程噪声的相关量和测量噪声之间的相关量，增加了描述多传感器融合系统的信息量。
The method presents the parametric expression for the gain matrix of the high-order PI observer. The contained parameters satisfy the needs of two constraints and are completely free as well.
该参数化方法给出了该类观测器增益矩阵的参数化表达式，其所含参数除了满足两个约束条件之外是完全自由的。
The advantage of the proposed method is that the stability of the reconfigured system can be guaranteed, and the algorithm for calculating the output feedback gain matrix is relatively simple.
这种方法的优点是重构系统的稳定性可得到保证，且计算输出反馈增益阵的算法相对简单。
Thereinto, for the spectral decomposition estimate of the covariance matrix , we can gain the risk functions under some losses.
其中，对于观测向量协方差阵的谱分解估计，我们很容易得到它在一些损失下的风险函数。
This method presents the parametric expressions for the gain matrices and the left eigenvector matrix of the high-order PI observers.
该方法给出了该类观测器的增益矩阵和左特征向量矩阵的参数化表达式。
The controller to be designed is assumed to have state feedback gain variations. Design methods are presented in terms of linear matrix inequalities (LMIs).
假定所要设计的控制器存在状态反馈增益变化，设计方法是以线性矩阵不等式组的形式给出的。
The problem of guaranteed cost control for a class of uncertain time-delayed systems was addressed. The uncertainties existed both in the systematic matrix, and in the controller gain.
研究了一类不确定时滞系统的保性能控制问题，其不确定性不仅存在于系统矩阵，而且存在于控制器的增益中。
Then, an algorithm based on iterative linear matrix inequality (ILMI) was proposed to compute the static output feedback gain of continuous uncertain T-S closed-loop fuzzy system.
为了计算连续不确定T - S闭环模糊系统的静态输出反馈增益，提出了基于迭代线性矩阵不等式的算法。
This paper points out that we can use the density function of the Gaussian distribution to set a thinned array, extending the covariance matrix will advance the gain clearly.
提出利用高斯随机分布的密度函数设置稀疏阵列，在稀疏阵列得到的协方差矩阵经扩展后，增益有了明显的提高。
This paper points out that a thinned array can be set with the density function of the Gaussian distribution, after the extending of covariance matrix the gain can be increased clearly.
提出利用高斯随机分布的密度函数设置稀疏阵列，稀疏阵列得到的协方差矩阵经扩展后，增益会有明显的提高。
Sufficient conditions for the existence of fuzzy state feedback gain and fuzzy observer gain are derived through the numerical solution of a set of coupled linear matrix inequalities(LMI).
用矩阵不等式给出了模糊反馈增益和模糊观测器增益的存在的充分条件，并将这些条件转化为线性矩阵不等式（LMI）的可解性。
The gain matrices of the output feedback controller are also constructed by means of the method of matrix decomposition.
的输出反馈控制器的增益矩阵的矩阵分解的方法，通过构造的。
Since the calculation of the matrix of Kalmann filter gain is not necessary, this method does not only reduce the cost of computation, but also ensure a good fil...
由于不需要实时的计算卡尔曼滤波的增益矩阵，此方法大大的降低了运算量，并仍能保证较高的滤波精度。
Since the calculation of the matrix of Kalmann filter gain is not necessary, this method does not only reduce the cost of computation, but also ensure a good fil...
由于不需要实时的计算卡尔曼滤波的增益矩阵，此方法大大的降低了运算量，并仍能保证较高的滤波精度。
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