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.     

基于LMI的随动系统满意PID调节器设计

PID控制器在实际工程中应用广泛,而且工程上对随动系统的性能要求往往是多方面的．该文应用满意控制思想,研究了期望指标：扇形区域极点,稳态输出方差和动态误差系数约束下随动系统的PID控制设计问题．首先将PID控制参数设计转化为局部状态反馈问题,导出了3项指标约束的双线性矩阵不等式(BMI)描述．然后给出改进的迭代线性矩阵不等式(LMI)算法求解BMI可行解,得到使闭环系统满足3项期望指标的PID参数．最后给出了应用该方法数值算例．     

反馈控制系统多性能约束指标的相容性

对一类线性随机系统的状态反馈控制, 研究极点配置指标、被控输出对范数有界外扰的H_∞抑制指标及稳态状态方差上界指标的相容性, 希望为实际控制系统多性能指标的选定提供理论依据, 用线性矩阵不等式(LMI)方法分别刻画了极点指标约束下H_∞指标的取值范围、以及相容极点指标和H_∞指标约束下稳态方差上界指标的取值范围, 对上述三类相容指标约束的控制问题给出求取满意控制策略的有效方法. 文中结论用数值算例作了说明.     

满足H∞,区域极点和方差指标约束的动态输出反馈控制研究

根据满意控制的思想，设计动态输出反馈控制器参数，使连续线性随机系统满足预先给定的H∞指标、扇形区域极点指标和协方差上界指标，以保证系统具有期望的性能。首先建立一个使闭环系统满足扇形区域极点指标的充分条件，然后利用线性矩阵不等式方法，将上述3类指标约束的动态输出反馈控制器设计问题转化成一组LMI的可行解问题， 后可借助Matlab-LMI工具箱进行有效求解。数值算例说明了所提出设计方法的有效性。     

模糊系统H∞控制器设计的LMI方法

应用LMI(线性矩阵不等式)方法,研究了T-S模糊系统H_∞控制器的设计问题.首先给出了T-S模糊系统基于状态反馈H_∞控制存在的两个新的充分条件.新条件不但简洁而且把模糊子系统间的相互作用表示为由子系统的系数矩阵构成的矩阵不等式.然后新条件被转化为可直接应用Matlab求解的线性矩阵不等式.最后应用线性矩阵不等式方法和Matlab,给出了T-S模糊系统H_∞控制器的设计方法.     

不确定时滞系统的时滞依赖鲁棒非脆弱H∞控制

基于线性矩阵不等式(LMI)方法, 研究了不确定时滞线性系统的鲁棒非脆弱H_∞状态反馈控制器的设计问题, 以一个LMI形式给出了控制器存在的充分条件, 而且该LMI是与时滞相关的. 同时, 经过全等变换、变量变换和Schur补引理, 该LMI的所有参数都是线性的, 这样参数无需预取就可以利用LMI Toolbox获得解. 实例表明了上述设计方法的有效性.     

不确定广义系统鲁棒镇定控制器的设计

讨论了线性定常广义系统的稳定性, 给出了这种系统H_∞ 范数形式的稳定性判据, 在此基础上, 利用线性矩阵不等式 (LMI)方法讨论了含有不确定参数的线性广义控制系统的鲁棒镇定问题, 并相应地给出了鲁棒镇定控制器的设计.     

一类非线性时滞广义系统的状态反馈控制

利用线性矩阵不等式(LMI),讨论了一类非线性时滞广义系统的状态反馈控制问题.通过对非线性映射Frechet导数的逆矩阵的估计,给出了系统渐近稳定的充分条件.这一条件与时滞相关,可归结为一个线性矩阵不等式的可解性.在LMI有解的条件下,可得到系统状态反馈控制器的参数表示.数值实例表明该方法是有效的.     

期望指标下一类线性周期系统鲁棒状态估计

针对满足多重区域指标约束的鲁棒滤波问题 ,以离散线性周期系统为研究对象 ,利用周期系统参数在某区间变化的特性 ,将周期系统满足极点或极点 /协方差指标的估计问题转化为区间系统的鲁棒估计问题。采用线性矩阵不等式 (L MIs)法进行凸优化 ,求解对应区间系统的满意估计增益 ,并设计相应鲁棒状态估计器。数值算例验证了相关的结论。     

一类多通道不确定时滞大系统分散鲁棒H∞控制：LMI方法

研究多通道不确定时滞大系统的鲁棒分散H_∞控制问题. 假定不确定性是时不变、范数有界, 且存在于系统、时滞和输出矩阵中. 主要针对动态输出反馈控制问题. 基于Lyapunov稳定性理论, 通过设定Lyapunov矩阵为合适的块对角结构, 采用矩阵替换的方法推导出了使多通道不确定时滞大系统可鲁棒镇定, 且满足一定的扰动水平的时滞依赖充分条件即线性矩阵不等式(LMI) 有可行解, 并且给出了具有期望阶数的分散鲁棒控制器的设计方法. 数值例子说明了本文提出方法的有效性.     

Satisfactory control of discrete-time linear periodic systems

In this paper satisfactory control for discrete-time linear periodic systems is studied. Based on a suitable time-invariant state sampled reformulation, periodic state feedback controller has been designed such that desired requirements of steady state covariance, H-infinity rejection bound and regional pole assignment for the periodic system are met simultaneously. By using satisfactory control theory, the problem of satisfactory periodic controller can be transformed into a linear programming problem subject to a set of linear matrix inequalities （LMIs）, and a feasible designing approach is presented via LMI technique. Numeric example validates the obtained conclusion.     

一类受扰线性采样数据系统的鲁棒执行器故障估计

针对一类含有外部干扰的线性采样数据系统, 本文研究了执行器故障估计问题. 首先, 文章设计了一种用于估计系统执行器故障的鲁棒故障估计观测器, 在连续采样时间间隔内, 观测器增益矩阵指数变化. 之后, 通过联合增广状态估计误差与故障误差, 并利用Lyapunov-Krasovskii泛函和线性矩阵不等式技术, 给出了保证误差系统全局渐近稳定的充分条件. 同时, 建立的线性矩阵不等式条件涉及调谐参数和最大采样间隔, 可以较好改善状态和故障估计性能. 最后, 通过对某型民航飞机模型实例进行仿真, 验证了本文所提方法具有更好的跟踪效果     

Adaptive variable structure state estimation for uncertain systems with persistently bounded disturbances

This paper develops an adaptive state estimator design methodology for nonlinear systems with unknown nonlinearities and persistently bounded disturbances. In the proposed estimation scheme, the boundary layer strategy in variable structure techniques is utilized to design a continuous state estimator such that the undesirable chattering phenomenon is avoided; and the adaptive bounding technique is used for online estimation of the unknown bounding parameter. The existence condition of the adaptive estimators is provided in terms of linear matrix inequality (LMI). Since the orthogonal projection of the state estimation error onto the null space of the linear measurement distribution matrix is used in the derivation process, the update law of bounding parameter estimate is represented in terms of the available measurement error. The proposed estimator can ensure that the state estimation error is uniformly ultimately bounded (UUB) with an ultimate bound. Furthermore, using the existing LMI optimization technique, a suboptimal adaptive state estimator can be obtained in the sense of minimizing an upper bound of the peak gains in the ultimate bound. Finally, a simulation example is given to illustrate the effectiveness of the proposed design method. Copyright © 2010 John Wiley & Sons, Ltd.     

Robust adaptive neural observer design for a class of nonlinear parabolic PDE systems

A robust adaptive neural observer design is proposed for a class of parabolic partial differential equation (PDE) systems with unknown nonlinearities and bounded disturbances. The modal decomposition technique is initially applied to the PDE system to formulate it as an infinite-dimensional singular perturbation model of ordinary differential equations (ODEs). By singular perturbations, an approximate nonlinear ODE system that captures the dominant (slow) dynamics of the PDE system is thus derived. A neural modal observer is subsequently constructed on the basis of the slow system for its state estimation. A linear matrix inequality (LMI) approach to the design of robust adaptive neural modal observers is developed such that the state estimation error of the slow system is uniformly ultimately bounded (UUB) with an ultimate bound. Furthermore, using the existing LMI optimization technique, a suboptimal robust adaptive neural modal observer can be obtained in the sense of minimizing an upper bound of the peak gains in the ultimate bound. In addition, using two-time-scale property of the singularly perturbed model, it is shown that the resulting state estimation error of the actual PDE system is UUB. Finally, the proposed method is applied to the estimation of temperature profile for a catalytic rod.     

基于LMI的一类非线性多时滞系统的模糊H∞滤波器设计

This paper develops fuzzy H1 filter for state estimation approach for nonlinear discrete-time systems with multiple time delays and unknown bounded disturbances. We design a stable fuzzy H1 filter based on the Takagi-Sugeno (T-S) fuzzy model, which assures asymptotic stability and a prescribed H1 index for the filtering error system. Sufficient condition for the existence of such a filter is established by solving the linear matrix inequality (LMI) problem. The LMI problem can be efficiently solved with global convergence using the interior point algorithm. Simulation examples are provided to illustrate the design procedure of the proposed method.     

Robust fault diagnosis for non-linear difference-algebraic systems

A new robust fault diagnosis method based on linear matrix inequality (LMI) for non-linear difference-algebraic systems (DAS) with uncertainties is proposed. Based on the known nominal model of DAS, it firstly constructs an auxiliary system consisting of a difference equation and an algebraic equation, then converts the problem of fault identification into the problem of parameter estimation, and finally realizes fault identification using an LMI method. This method can not only detect, isolate and identify faults for DAS, but also give the upper bounds of fault identification error. Simulation indicates that it can give satisfactory diagnostic results for both abrupt and incipient faults.     

Unknown inputs observer for a class of nonlinear uncertain systems: An LMI approach

This paper deals with the simultaneous estimation of states and unknown inputs for a class of Lipschitz nonlinear systems using only the measured outputs. The system is assumed to have bounded uncertainties that appear on both the state and output matrices. The observer design problem is formulated as a set of linear constraints which can be easily solved using linear matrix inequalities (LMI) technique. An application based on manipulator arm actuated by a direct current (DC) motor is presented to evaluate the performance of the proposed observer. The observer is applied to estimate both state and faults.     

OBSERVER-BASED STABILIZATION OF SYSTEMS WITH MONOTONIC NONLINEARITIES

We design an observer-based control law for a class of systems that include monotonic nonlinearities of the unmeasured states. Our observer results in nonlinear error dynamics which can be represented as the feedback interconnection of a linear system and a time-verying multivariable sector nonlinearity. The convergence of the estimation error is guaranteed by an observer matrix that renders the linear part passive, and is computable with LMI software. The feedback design is completed by combining the observer with a control law that renders the plant input-to-state stable with respect to the state estimation error.