不确定时滞系统的鲁棒H∞滤波

对一类同时具有外界干扰和范数有界参数不确定性的时滞系统鲁棒H∞滤波问题进行了研究。对于所有容许的参数不确定性,利用Lyapunov方法,得到以线性矩阵不等式（linear matrix inequality,LMI）表示的鲁棒H∞滤波器设计方法。用该方法设计的滤波器使得滤波误差系统渐近稳定且满足一定的H∞性能指标。给出了滤波器存在的充分条件,并得到了设计滤波器的LMI方法。进而将最优鲁棒H∞滤波器存在的充分条件归结为一个具有线性矩阵不等式（LMI）约束的凸优化问题。最后,仿真结果很好地说明了本文方法的有效性。     

具有随机一步时延及丢包的离散系统H∞滤波

针对存在随机一步时延及丢包的网络,研究了一类离散系统的H∞滤波问题。时延及丢包被认为是两个Bernoulli随机序列,利用线性矩阵不等式(LMI)方法给出了滤波器存在的充分条件,所设计的滤波器使得滤波误差系统在均方意义下是指数稳定的且满足给定的H∞性能。滤波器参数通过凸优化求解一个线性矩阵不等式获得。     

不确定线性周期系统的满意滤波

针对线性周期多采样率系统的满意滤波问题,根据满意估计思想,将结构不确定周期系统满足滤波系统稳定与H∞指标的满意估计问题转化为Riccati矩阵不等式求解问题,无须采用通常的提升手段而直接运用数值法与内点法进行周期系统多指标设计.利用线性矩阵不等式技术(LMI)提出了一种基于LMI的满意滤波器设计方法.仿真例子验证了相关的结论.     

具有随机通讯时延的离散网络化系统的H∞滤波器设计

由于传感器和滤波器是通过有限带宽的网络连接的,因此系统的测量数据经常会出现时延,而且时延是随机的.本文讨论了具有一步随机通讯时延的离散网络化系统的H∞滤波器设计问题.利用线性矩阵不等式方法设计线性滤波器使得滤波误差系统是均方意义下指数稳定并具有给定的H∞性能.滤波器参数通过凸优化技术求解一个线性矩阵不等式得到.数值仿真表明设计方法的有效性.     

一类网络控制系统的非脆弱耗散滤波器设计

针对网络化控制系统的滤波器参数存在摄动的问题,考虑到传感器-滤波器存在随机时延和丢包,设计对系统待估信号进行估计的加性非脆弱耗散滤波器,其中滤波器参数具有范数有界不确定性。首先使用Lyapunov稳定性理论和线性矩阵不等式分析方法,推导出耗散滤波器存在的充分条件,在此基础上考虑到滤波器参数不确定性,从而将非脆弱耗散滤波问题转化为求解线性矩阵不等式的问题,然后通过求解线性矩阵不等式得到非脆弱耗散滤波器的参数表达式,最后数值仿真验证了设计方法的有效性。     

具有椭圆盘极点约束的线性系统滤波器设计

针对一类线性系统,研究其闭环系统极点具有椭圆盘约束的情况下滤波器设计问题。在极点约束的前提下,控制目标要求闭环系统渐近稳定,并且干扰抑制性能指标小于给定的上界。首先利用有界实引理给出椭圆盘极点约束前提下滤波器的存在条件;其次,利用线性矩阵不等式技术,将滤波器的存在性问题转化成一组线性矩阵不等式(LMI)的可行性问题,根据LMI的可行解,给出滤波器的设计方法,由该方法得到的滤波器满足给定的性能要求;最后,数值算例说明该方法的有效性和可行性。     

LMI工具箱及其在控制相关领域的应用

随着计算机计算性能的不断增强,凸优化问题则可以通过求解高阶的矩阵不等式的方式来解决,从而在控制系统及相关领域中,线性矩阵不等式(LMI)得以广泛应用.在控制系统的分析与设计中,LMI扮演着越来越重的角色.介绍了LMI的相关理论,给出了在Matlab软件及LMI工具箱中的3类标准问题的求解器,并结合示例说明了它应用方法.     

一类非线性随机不确定系统有限时间H∞无穷滤波

研究一类具有时变、有界干扰的非线性随机不确定系统有限时间H∞滤波问题.首先,给出了非线性随机不确定系统有限时间H∞滤波问题的定义;其次,通过构造Lyapunov-Krasoviskii函数,并结合线性矩阵不等式（LMI）方法,给出了非线性随机不确定系统有限时间∞滤波器存在的充分条件;再次,将该问题简化为具有LMI约束的优化问题,并给出了相应的求解算法;最后,通过数值算例表明了所提出设计方法的有效性.     

不确定广义系统的弹性H∞保性能控制

利用线性矩阵不等式(LMI)方法,研究被控对象与控制器同时存在摄动的H∞保性能控制问题.针对控制器存在加法式摄动情形,以线性矩阵不等式约束条件给出了广义系统弹性H∞保性能的充分条件,并以线性矩阵不等式的可行解给出了相应的控制器设计方法.通过求解具有线性矩阵不等式约束的凸优化问题,给出了弹性H∞最优保性能及最优H∞性能控制器的设计方法.仿真表明了方法的可行性.     

一种基于LMI的鲁棒故障诊断滤波器设计

研究了一类含有扰动的线性系统鲁棒故障诊断滤波器设计问题. 文中引入一种能同时体现残差对扰动信号鲁棒性和对故障信号灵敏性的性能指标, 利用H_∞理论把求解滤波器的问题转化为H_∞优化设计问题. 应用线性矩阵不等式(LMI)技术, 对此性能指标进行优化, 给出并证明了该设计问题解的存在性条件和滤波器增益阵的求解方法, 最后, 通过仿真实例验证了方法的有效性.     

An LMI approach to design robust fault detection filter for uncertain LTI systems

In this paper, the robust fault detection filter design problem for uncertain linear time-invariant (LTI) systems with both unknown inputs and modelling errors is studied. The basic idea of our study is to use an optimal residual generator (assuming no modelling errors) as the reference residual model of the robust fault detection filter design for uncertain LTI systems with modelling errors and, based on it, to formulate the robust fault detection filter design as an H_∞ model-matching problem. By using some recent results of H_∞ optimization, a solution of the optimization problem is then presented via a linear matrix inequality (LMI) formulation. The main results include the development of an optimal reference residual model, the formulation of robust fault detection filter design problem, the derivation of a sufficient condition for the existence of a robust fault detection filter and a construction of it based on the LMI solution parameters, the determination of adaptive threshold for fault detection. An illustrative design example is employed to demonstrate the effectiveness of the proposed approach.     

An ILMI Approach to RFDF for Uncertain Linear Systems with Nonlinear Perturbations

The robust fault detection filter design for uncertain linear systems with nonlinear perturbations is formulated as a two-objective optimization problem. Solvable conditions for the existence of such a robust fault detection filter are given in terms of matrix inequalities (MIs), which can be solved by applying iterative linear matrix inequality (ILMI) techniques. Particularly, compared with two existing LMI methods, the developed algorithm is more generalized and less conservative. An illustrative example is given to show the effectiveness of the proposed method.     

非线性摄动系统的鲁棒故障诊断滤波器设计ILMI算法

The robust fault detection filter design for uncertain linear systems with nonlinear perturbations is formulated as a two-objective optimization problem. Solvable conditions for the exis- tence of such a robust fault detection filter are given in terms of matrix inequalities (MIs), which can be solved by applying iterative linear matrix inequality (ILMI) techniques. Particularly, compared with two existing LMI methods, the developed algorithm is more generalized and less conservative. An illustrative example is given to show the effectiveness of the proposed method.     

Design and analysis of robust fault detection filter using LMI tools

In this paper, the robust fault detection filter design problem for linear time invariant (LTI) systems with unknown inputs and modeling uncertainties is studied. The basic idea of our study is to formulate the robust fault detection filter design as a H_∞ model-matching problem. A solution of the optimal problem is then presented via a linear matrix inequality (LMI) formulation. The main results include the formulation of robust fault detection filter design problems, the derivation of a sufficient condition for the existence of a robust fault detection filter and construction of a robust fault detection filter based on the iterative of LMI algorithm.     

ℋ 2 filtering of discrete-time Markov jump linear systems through linear matrix inequalities

This paper addresses the ?₂ filtering design problem of discrete-time Markov jump linear systems. First, under the assumption that the Markov parameter is measured, the main contribution is on the LMI characterisation of all filters such that the estimation error remains bounded by a given ?₂ norm level, yielding the complete solution of the mode-dependent filtering design problem. Based on this result, a robust filter design to deal with convex bounded parameter uncertainty is considered. Second, from the same LMI characterisation, a design procedure for mode-independent filtering design is proposed. Some examples are solved for illustration and comparison.     

${cal H}_{infty}$ Filtering of Discrete-Time Markov Jump Linear Systems Through Linear Matrix Inequalities

This technical note addresses the discrete-time Markov jump linear systems ${cal H}_{infty}$ filtering design problem. First, under the assumption that the Markov parameter is measurable, the main contribution is the linear matrix inequality (LMI) characterization of all linear filters such that the estimation error remains bounded by a given ${cal H}_{infty}$ norm level, yielding the complete solution of the mode-dependent filtering design problem. Based on this result, a robust filter design able to deal with polytopic uncertainty is considered. Second, from the same LMI characterization, a design procedure for mode-independent filtering is proposed. Some examples are solved for illustration and comparisons.