广义线性系统的干扰解耦观测器设计

提出了广义线性系统的Luenberger函数观测器关于干扰解耦的充要条件,并进一步基于广义Sylvester矩阵方程的显式通解给出了干扰解耦观测器的参数化设计方法.这种方法首先给出了观测器增益矩阵的参数表示,然后通过结合观测器增益矩阵的参数表示和提出的干扰解耦条件,给出了设计广义线性系统干扰解耦观测器的算法.数值例子说明了本文设计方法的有效性.     

一种鲁棒故障检测与分离的参数化方法

针对具有未知干扰输入的多变量线性系统,提出一种鲁棒故障检测与分离的完全参数化方法。利用最近的结果,基于Luenberger未知输入观测器矩阵的特征值及一组自由参数向量,分别给出了系统干扰解耦和故障分离的充要条件。通过适当选择满足一些约束的自由参数,仅使用单一观测器实现了鲁棒故障检测与分离设计。该方法提供了所有设计自由度。一个数值例子证明了该方法的有效性。     

线性系统的干扰解耦观测器设计

此文提出线性系统的Luenberger函数观测器关于干扰解耦的条件,指出它与环路复现 (LTR)的关系.并结合Luenberger观测器设计的一种参数化方法,给出了线性系统干扰解 耦Luenberger观测器的一种简单、有效的设计方法.     

离散线性系统高阶积分观测器设计

针对离散线性系统提出一类高阶积分观测器。并且显示这类观测器满足极点配置分离原理，同时给出了这类观测器的存在条件．基于Sylvester矩阵方程的显式参数化通解提出了这类观测器的参数化设计方法．该方法不仅给出了观测器增益矩阵的参数表达式，而且还提供了观测器系统矩阵左特征向量的参数表达式．该设计方法给出了所有的设计自由度，为实现系统的其他性能提供了方便且强有力的工具．数值例子说明了设计过程，并表明了该方法的有效性．     

基于观测器的参数不确定系统降阶H_∞控制器设计

本文研究了Luenberger观测器的参数不确定系统降阶H∞控制器设计问题,提出了参数不确定系统H∞状态反馈控制问题的一个充要条件,并利用线性矩阵不等式方法求解出参数不确定系统的H∞状态反馈增益。然后对该H∞状态反馈增益进行渐进降阶观测,基于广义Sylverster方程显式通解的参数化设计方法,实现了参数不确定系统的降阶H∞控制。     

二阶线性系统全维PI观测器的参数化设计

基于一类广义Sylvester矩阵方程的解．提出了二阶线性系统的全维PI观测器设计参数化方法．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．该观测器设计的参数化方法直接基于二阶线性系统的参数矩阵，不涉及系统的变换或增广．数值例子表明了所提方法的简单有效性．     

二阶动力学系统高阶PI观测器的参数化设计方法

本文研究二阶动力学系统的高阶比例积分(PI)观测器设计问题．基于Sylvester矩阵方程的解，提出了该观测器设计的参数化方法．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．这些参数为控制系统设计提供了全部自由度，可通过优化等手段选择这些参数来满足某些性能要求，如干扰解耦、故障检测和鲁棒性等．此外，该PI观测器的参数化设计方法直接利用二阶动力学系统的原始参数矩阵，只涉及二阶动力学系统n维参数矩阵的运算．给出一个数值例子，以说明所提方法的简单性和有效性．     

一类非线性奇异系统的观测器设计

讨论了一类局部可观测的非线性奇异系统,首先基于非线性坐标变换进行完全线性 化,然后再用类似Luenberger方法进行降阶观测器设计.仿真结果表明了该方法的有效性.     

鲁棒Luenberger观测器设计

观测器控制系统中的观测器条件是系统的状态观测值渐近收敛于系统真实状态的根本 条件.本文首先提出了Luenberger观测器设计的一种参数方法,然后根据使观测器条件误差 为最小的准则,考虑了具有参数摄动的系统的鲁棒Luenberget观测器设计问题,给出了简单、 有效的算法.仿真结果说明了本文方法的有效性.     

矩阵方程AX-EXF=BY的通解及其应用

给出矩阵方程AX—EXY=BY的一个完全解析的、具有显式表达式和完全自由度的参数解(X,Y)．这里假设矩阵束(E,A B)为R-能控的,F为任意的方阵．相比于现有结论,求解算法不要求矩阵A和F具有特殊的形式,且对它们的特征值没有任何的限制,此外,本文给出的通解还具有结构简洁的特点,作为一个应用,给出了广义系统正常Luenberger函数观测器的一种参数化的设计方法,算例证明了方法的有效性．     

Robust fault detection in linear systems based on PI observers

A parametric approach for robust fault detection in linear systems with unknown disturbances is presented. The residual is generated using full-order proportional-integral (PI) observers. The approach is based on a result for PI observer design recently proposed. In terms of the design degrees of freedom provided by the parametric PI observer design and a group of introduced parameter vectors, a sufficient and necessary condition for PI observer design with disturbance decoupling is established. By properly constraining the design parameters according to this proposed condition, the effect of the disturbance to the residual signal is decoupled, and a simple algorithm is presented. The presented approach offers all the degrees of design freedom. A numerical example illustrates the effect of the proposed approach.     

Robust fault detection using Luenberger-type unknown input observers-a parametric approach

A new parametric observer-based approach for robust fault detection in multivariable linear systems with unknown disturbances is proposed. The residual is generated through utilizing a Luenberger function observer. By using a parametric solution to a class of generalized Sylvester matrix equations, a parametrization is proposed for the residual generator on the basis of a Luenberger function observer. By further properly constraining the design parameters provided in the Luenberger observer design, the effect of the unknown disturbance is decoupled from the residual signal. The proposed approach provides all the degrees of freedom and is demonstrated to be simple and effective.     

Robust fault detection in linear systems based on full-order state observers

A parametric approach to robust fault detection in linear systems with unknown disturbances is presented. The residual is generated using full-order state observers （FSO）. Based on an analytical solution to a type of Sylvester matrix equations, the parameterization of the observer gain matrix is given. In terms of the design degrees of freedom provided by the parametric observer design and a group of introduced parameter vectors, a sufficient and necessary condition for fullorder state observer design with disturbance decoupling is then established. By properly constraining the design parameters according to this proposed condition, the effect of the disturbance on the residual signal is also decoupled, and a simple algorithm is developed. The presented approach offers all the degrees of design freedom. Finally, a numerical example illustrates the effect of the proposed approach.     

Robust fault detection in linear systems based on full-order state observers

A parametric approach to robust fault detection in linear systems with unknown disturbances is presented. The residual is generated using full-order state observers (FSO). Based on an analytical solution to a type of Sylvester matrix equations, the parameterization of the observer gain matrix is given. In terms of the design degrees of freedom provided by the parametric observer design and a group of introduced parameter vectors, a sufficient and necessary condition for fullorder state observer design with disturbance decoupling is then established. By properly constraining the design parameters according to this proposed condition, the effect of the disturbance on the residual signal is also decoupled, and a simple algorithm is developed. The presented approach offers all the degrees of design freedom. Finally, a numerical example illustrates the effect of the proposed approach.     

Eigenstructure assignment design for proportional-integral observers: the discrete-time case

A complete parametric design approach for proportional-integral observers of multivariable discrete-time linear systems is proposed based on an eigenstructure assignment technique. Complete parameterizations for all the observer gains as well as the eigenvector matrix of the observer system matrix are established in terms of three sets of design parameters that satisfy three basic and simple constraints. The proposed approach provides all the degrees of freedom and has great potential in applications. An illustrative example shows the effect of the proposed approach.