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In the thesis , firstly the problem of static output feedback H∞control was explored for discrete time singular systems. Based on the generalized Riccati inequality and linear matrix inequality, necessary and sufficient conditions were obtained for the existence of static output feedback H∞controllers, which guarantees that the resulting closed-loop system is admissible with its transfer function matrix satisfying H∞norm constraint.

本文首先利用线性矩阵不等式和广义Riccati不等式,给出离散广义系统中存在静态输出反馈H∞控制器,使得闭环系统是容许的且其传递函数矩阵满足H∞范数约束的充要条件。

The common method, that all strong-correlation terms of the model are eliminated, can bring the loss in the engineering application, so the new method is proposed that the identified model reserves some correlation. The augmented matrix A is constructed by the outputΔW and the matrix S. The"determinating order based on ratio of determinant"is brought out to screen the strong-correlation terms in the structure identification. The latent root estimation is improved in screening the eigenvalues and eigenvectors. Thus the estimation precision is improved greatly.The consistence check of guidance instrument error coefficients of flight test and ground test is the purpose of flight experiment. The causes of inconsistency of the two models are analyzed. The hypothesis test of linear regression model based on F statistics is proposed to check the consistence.Finally, the instability of error coefficients is probably caused by the change of the flight environments, therefore, the relation between the error coefficients and flight environment is analyzed. The approach is presented to identify SINS guidance instrument error models and compensate the error in the segmented sections corresponding to the change of vertical acceleration of aircraft.

在结构辨识中,常用的方法由于将模型中的强相关项全部剔除而给工程应用带来损失,因此,本文提出了新的有益思想,即在保留一定相关性的基础上进行辨识:将输出向量ΔW与环境函数矩阵S构成增广矩阵A,然后采用"比定阶行列式"来剔除相关向量的方法,这样既可以尽可能多地保留了对落点影响大的强相关参数,又可以对落点影响小的强相关参数给予剔除;在参数估计中,改进了特征根估计中特征根和特征向量的筛选方法,提出"近零"准则,从而大大提高了参数估计的精度;再者,鉴于天地模型"一致性"检验是飞行试验和SINS制导工具误差系数分离的主要目的,因此,本文又深入分析了造成天地模型不一致的原因,提出了采用基于F统计的线性回归模型假设检验方法来进行捷联制导工具误差模型的天地"一致性"检验;最后,鉴于飞行环境剧烈变化可能会对惯性仪表误差系数稳定性带来一定的影响,因此本文深入地分析了SINS制导工具误差系数与外界环境的关系,提出了基于过载变化大小的分段辨识和分段实时补偿的算法。

In the end, the PID diagonal matrix decoupling control algorithm was adopted in the system based on the matrix transfer function, and it is compared with reverse-forward-feed decoupling method.

最后根据系统的传递函数矩阵,采用PID对角矩阵解耦控制算法实现其解耦控制,并将其与反前馈解耦算法作了比较。

Matrix expression of acoustic field and Green's function are introduced in detail.

对声场的简正波形式的矩阵表达式以及声场格林函数矩阵进行了详细介绍。

The so-call'exportable equation'is found by nonlinear geometry method for general non-autonomous chaotic control systems which coefficient matrix of control term is functional matrix contained system variables. The homeomorphic transformation of coordinate is found under specified conditions, the coefficient matrix of control term can be transformed as constant matrix, the synchronization among chaotic systems can be realized by common control methods.

针对一般的非自治混沌控制系统中控制项系数矩阵是含有系统变量的函数矩阵,利用非线性几何线性化的方法找出所谓的"输出方程",在一定的条件下求出坐标的同胚变换,将控制项系数矩阵变换为常矩阵,然后利用常规的控制方法进行混沌系统之间的同步化。

In the method,thematrix exponential is calculated precisely by using 2N algorithm and the integration offunctional matrix by parts is applied.

首先依据常微分方程的经典理论,运用指数矩阵的2N类精细算法及函数矩阵的分部积分法建立数值求解常微分方程的一般方法。

In chapter 2, first of all,we characterize subspace V_0 of multiresultion analysis {V_j}_~ based on invariant subspace. Subsequently, we consider the equivalent conditions among orthogonal multiwavelet Ψ=(Ψ_1,Ψ_2,...Ψ_r)~T, subspace, basis and dimension of subspace, properties of filter function matrix P are dealt with.

第二章讨论了多尺度分析{V_j}_~中子空间V_0的性质,进而讨论了多尺度分析生成的多重正交小波Ψ=(ψ_1,ψ_2,…,ψ_r)~T和子空间V_0以及基和维数之间的等价关系,分析了滤子函数矩阵P的性质,最后给出了r阶矩阵函数P生成尺度函数Φ的充分条件。

This paper presents the construction of the shape functions using the monomial basic function and describes the properties of the shape functions.

本文研究了点插值法中以单项式为基函数的形函数的建立及其性质,并通过矩阵三角化算法来克服形函数矩阵大奇异性。

Upon the conditions addressed,an improved parameter-dependent l2-l∞ performance criterion is established by the introduction of a slack variable,which exhibits a kind of decoupling between Lyapunov functions and system matrices.

同时应用投影定理,通过引入附加矩阵变量,解除了系统矩阵与依赖于参数的Lyapunov函数矩阵之间的耦合,使所得到的条件更适合于滤波器的综合。

How to calculate precisely the circumstance function matrix for the gimbaled system is lucubrated. The method of using exterior data and the method of calculating iteratively are put forward. The simulation result shows that two methods can increase the calculating accuracy of the circumstance function matrix.

讨论了平台式系统环境函数矩阵的精确计算问题,提出了利用外测数据与应用迭代技术精确计算环境函数矩阵的方法,仿真计算表明,这两种方法能够有效提高环境函数的计算精度。

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