ID 原文 译文
49076 研究了一类输入饱和T-S模型的扰动抑制问题。 For a class of input saturation disturbance rejection problem of t-s model.
49077 采用分区讨论与大中取大综合方法处理饱和项,利用Lyapunov稳定性理论,提出了非线性系统的执行器饱和控制器存在的充分条件,进一步对控制器进行了优化,以实现扰动抑制要求。 Using partition discussion and large and medium-sized take large comprehensive treatments of saturated, using Lyapunov stability theory, put forward the nonlinear system of a sufficient condition for the existence of the actuator saturation controller, the controller is optimized further, to achieve the requirements of disturbance rejection.
49078 通过简单变换,将该条件转化为Matlab易于求解的线性矩阵不等式。 Through a simple transform, Matlab is easy to solve the condition can be converted to linear matrix inequality (lmi).
49079 最后,对Lurie系统的控制仿真验证了该方法的有效性。 Finally, the control of the Lurie system simulation verified the effectiveness of the method.
49080 深入研究自组织网络体系结构建立的动机,针对现有网络体系结构中缺少对任务需求的耦合,提出面向任务能力的自组织网络体系结构,给出了包括量化任务、任务规划、平台分簇和分级结构4个阶段的设计过程,并针对每个阶段设计给出了数学描述,最后给出了组网的计算方法。 Further study of self-organizing network architecture establishing motivation, in view of the existing network structure coupled with the lack of demand for the task, task oriented ability of self-organizing network system structure, gives the quantitative mission, mission planning, including platform cluster and hierarchical structure of the four stages of the design process, and provides a mathematical description for each stage of design, finally gives the calculation method of networking.
49081 通过案例分析,展示了设计过程中的阶段结果和最终组网体系,并使用评估指标对所设计的组网体系进行了分析评估。 Through the case analysis, demonstrates the stage results in the design process and the final network system, and use the evaluation index to evaluate the designed network system are analyzed.
49082 Capon空间谱需要计算搜索方向矢量与训练样本协方差矩阵的广义内积值,要求有较高的协方差矩阵估计精度。 Capon spatial spectrum need to compute the search direction vector and the training sample covariance matrix of the generalized inner product value, require a higher precision of the covariance matrix.
49083 在训练样本较少且同时存在强弱临近目标条件下,采样协方差矩阵存在较大估计误差,使得空间谱分辨性能严重下降。 Exists weak near targets at the same time in the less training samples and conditions, the sampling covariance matrix is estimated error, makes the spatial spectral resolution serious decline in performance.
49084 提出自适应加权修正的改进方法,所提方法在重构数据协方差矩阵基础上,首先利用最小二乘方法估计搜索信号强度并修正数据协方差矩阵,然后计算搜索方向矢量在相应修正的数据协方差矩阵的广义内积值,最后利用该广义内积值对传统Capon空间谱进行自适应加权处理,在保持高分辨性能的同时降低了对样本数的要求,提高了临近强弱目标的稳健性。 Proposed adaptive weighted correction method, the proposed method is based on reconstructing the data covariance matrix, the first search signal strength is estimated based on the least squares method and correct the data covariance matrix, then calculate the search direction vector in the corresponding correction data covariance matrix of the generalized inner product value, finally using the generalized inner product value of traditional Capon spatial spectrum adaptive weighted processing, while maintaining high resolution reduces the requirement for sample at the same time, the performance of improved approaches of weak target robustness.
49085 理论分析和仿真结果表明所提方法在小训练样本条件下对临近强弱信号的分辨性能优于Capon方法。 Theoretical analysis and simulation results show that the proposed method under the condition of small training samples for near weak signal resolution performance is superior to the Capon method.