离散区间系统的二次稳定性及其稳定裕度分析

研究了动态离散区间系统的鲁棒稳定性问题,提出了系统二次稳定的充分与必要条件,以及相应的稳定裕度的计算方法,并推广到离散参数不确定系统.所有结论以线性矩阵不等式(LMI)的形式给出.利用功能强大的LMI工具,求解非常方便.所给实例表明,该方法用于确定动态离散区间系统的鲁棒稳定性及其稳定裕度,非常有效.     

区间矩阵二次稳定的充分必要条件

提出了区间矩阵二次稳定的充分必要条件,以及相应的稳定裕度的计算方法.结论以线性矩阵不等式(LMI)的形式给出.利用功能强大的LMI工具,求解非常方便.所给实例表明,该方法用于确定区间矩阵的鲁棒稳定性及其稳定裕度,非常有效.     

一类离散切换时滞非线性系统的H∞控制

研究一类基于神经网络的离散切换时滞非线性系统的稳定性和H∞控制问题。利用线性矩阵不等式方法得到了该类系统稳定性条件。在此基础上,通过引入一些变量讨论了该类系统的反馈控制器设计问题。以线性矩阵不等式的形式提出了该类系统反馈控制器的设计方法,并利用Matlab中的LMI工具箱直接求解。最后给出数值例子说明方法有效性。     

一类不确定系统的鲁棒稳定性分析

研究了一类不确定系统的稳定性问题, 以线性矩阵不等式(LMI)的形式给出了该类系统的鲁棒稳定条件, 并将该结果推广到区间系统的稳定性分析, 提出了研究区间系统稳定性问题的新方法, 给出了线性矩阵不等式形式的稳定判据, 该判据将区间系统的稳定性问题转化为一类线性矩阵不等式的可解问题. 最后通过仿真算例验证了本文结果具有更小的保守性.     

广义不确定周期时变系统的鲁棒稳定性分析

研究广义不确定周期时变系统的鲁棒稳定性问题.基于广义周期时变系统Lyapunov不等式,提出了广义不确定周期时变系统鲁棒稳定的概念,采用矩阵不等式(LMI)方法,得到了该类系统鲁棒稳定的充分必要条件;然后,进一步研究了在状态反馈控制下保证闭环系统鲁棒稳定的条件,给出了一族状态反馈鲁棒稳定器的设计方法;最后,引入了广义周期时变系统二次稳定的概念,并讨论了二次稳定性与鲁棒稳定性之间的关系.     

含时变滞后的不确定系统的时滞相关型鲁棒控制设计

研究含时变滞后的不确定系统的控制综合问题. 基于Lyapunov方法提出了一种含滞后补偿的鲁棒控制设计方法. 闭环稳定性条件由一组线性矩阵不等式表示. 在这些条件中给出了稳定性和滞后以及其导数之间的关系. 实例显示, 利用提供的方法所给出的结果比以往文献给出的结果保守性小.     

T-S型模糊系统的稳定性分析及其应用

讨论了状态空间形式下Ｔａｋａｇｉ和Ｓｕｇｅｎｏ提出的一类模糊系统的稳定性,利用矩阵范数和矩阵分析理论给出了判定该类系统稳定的新的充分条件。在此基础上分析了国产某飞机在地面滑行时纵向短周期运动的稳定性,比以往结论更加有效。     

一类多时滞非线性系统的稳定性研究

非线性系统的稳定性是目前自动控制理论研究的一个热点问题。本文通过构造多时滞非线性系统的李雅普诺夫函数,运用线性矩阵不等式方法,研究了一类不确定的时滞系统的稳定性问题,给出了该类系统鲁棒性稳定的充分条件。     

不确定广义线性时变系统的鲁棒稳定和二次稳定

针对不确定广义线性时变系统,采用矩阵不等式的分析方法,提出不确定广义线性时变系统鲁棒稳定和二次稳定的概念.建立该类系统的矩阵不等式,将该类系统的鲁棒控制问题转化为求解矩阵不等式问题,得到该类系统鲁棒稳定和二次稳定的充分必要条件,并给出一种状态反馈鲁棒镇定控制器的设计方法.最后,通过数值算例表明了所提出方法的可行性.     

比例型T-S模糊控制系统稳定性分析与设计

讨论了比例型T-S模糊控制系统(TSS)的稳定性与设计问题. 利用具有乘积可换性状态矩阵的T-S系统的公共P阵构造方法及鲁棒稳定域条件, 给出了TSS系统的满足全局Lyapunov稳定的正定矩阵P的递推求解方法, 并提出一种TSS模糊控制系统设计和稳定性分析的规范化方法.     

Model predictive control for constrained systems with uncertain state‐delays

This paper presents a model predictive control (MPC) algorithm for a class of constrained linear systems with uncertain state‐delays. Based on a novel artificial Lyapunov function, a new stabilizing condition dependent of the upper bound of uncertain state‐delays is presented in an LMI (linear matrix inequality) form. The proposed MPC algorithm is developed by following the fashion of stability‐enforced scheme. The new algorithm is then extended to linear time varying (LTV) systems with multiple uncertain state‐delays. Numerical examples illustrate the effectiveness of the new algorithm. Copyright © 2004 John Wiley & Sons, Ltd.     

Delay-range-dependent stability for uncertain stochastic systems with interval time-varying delay and nonlinear perturbations

This paper considers the problem of robust stability for a class of uncertain stochastic systems with interval time-varying delay under nonlinear perturbations. A new delay-dependent method for robust stability of the systems is proposed. The innovation of the method includes employment of a tighter integral inequality and construction of an appropriate type of Lyapunov–Krasovskii functional. The restriction used to bound some trace term in the existing methods is also removed. The resulting criterion derived from this method has advantages over previous ones in that it has less conservatism and enlarges the scope of application. The reduction in conservatism of the proposed criterion is attributed to a method to estimate the upper bound on the stochastic differential of the Lyapunov–Krasovskii functional without neglecting any useful terms in the delay-dependent stability analysis. On the basis of the estimation and by utilizing free-weighting matrices, new delay-range-dependent stability criterion is established in terms of linear matrix inequality. Finally, numerical examples are provided to show the effectiveness and reduced conservatism of the proposed method.     

具有时变状态滞后的非线性2-D 离散系统的稳定性与控制

考虑一类由局部状态空间Fornasini-Marchesini(FM LSS)第二模型描述的,具有时变状态滞后非线性二维(2-D)离散系统的稳定性分析和控制问题.时变状态滞后项的上、下界为正整数,非线性项满足Lipschitz条件.首先,通过引入一个含有时滞上、下界的新Lyapunov函数,给出了系统的稳定性准则;然后设计了状态反馈控制器以保证系统的稳定性,进而,状态反馈控制律可由线性矩阵不等式求得;最后通过数值算例表明了所得结果的有效性.     

具有滞后摄动的线性系统鲁棒稳定性分析

基于Ｌｙａｐｕｎｏｖ稳定性理论,导出了具有滞后时变摄动的线性系统二次稳定的一个充分必要条件,通过求解一个具有线性矩阵不等式约束的凸优化问题,得到了保持系统稳定的最大允许摄动界,文中的例子说明了：和现有的方法相比,本文提出的方法具有更小的保守性。     

Delay-interval-dependent robust-stability criteria for neutral stochastic neural networks with polytopic and linear fractional uncertainties

In this paper, the delay-interval-dependent robust stability is studied for a class of neutral stochastic neural networks with time-varying delays. The time-varying delay is assumed to belong to an interval, which means that the upper bound is known and the lower bound is not restricted to zero. For the neural networks under study, the uncertainty includes polytopic uncertainty and linear fractional norm-bounded uncertainty. Sufficient conditions for the stability of the addressed neutral stochastic neural networks with time-varying delays are established by employing the proper Lyapunov–Krasovskii functional, a combination of the stochastic analysis theory, some inequality techniques and new linear matrix inequality (LMI). Finally, three numerical examples are provided to demonstrate less conservatism and effectiveness of the proposed LMI conditions.     

基于新型 Abel 型有限和不等式的时滞系统稳定性判据

针对线性离散时滞系统的时滞相关稳定性问题进行研究,提出一个新的有限和不等式,是Abel型不等式的进一步推广.利用这一不等式和构造适当的Lyapunov-Krasovskii泛函,给出新的离散时滞系统稳定性判别准则,并应用数值例子进行验证.验证结果表明,所提出方法与Abel型不等式方法相比,能够获得更大的允许上界,比用自由权方法使用更少的决策变量,降低了数值计算负担,进一步表明了所得结果的有效性和优越性.     

Finite‐Time Stability and Stabilization of Linear Itô Stochastic Systems with State and Control‐Dependent Noise

In this paper, finite‐time stability and stabilization problems for a class of linear stochastic systems are studied. First, a new concept of finite‐time stochastic stability is defined for linear stochastic systems. Then, based on matrix inequalities, some sufficient conditions under which the stochastic systems are finite‐time stochastically stable are given. Subsequently, the finite‐time stochastic stabilization is studied and some sufficient conditions for the existence of a state feedback controller and a dynamic output feedback controller are presented by using a matrix inequality approach. An algorithm is given for solving the matrix inequalities arising from finite‐time stochastic stability (stabilization). Finally, two examples are employed to illustrate the results.     

多输入/多输出系统动态矩阵控制鲁棒稳定性

研究了基于脉冲响应模型的动态矩阵预测控制(DMC)算法,针对多输入、多输出(MIMO)系统脉冲响应模型的特点,利用脉冲响应系数误差矩阵范数平方和定义预测模型的模型误差,以线性矩阵不等式(LMI)的形式提出了DMC闭环鲁棒稳定充要条件,将DMC算法闭环稳定问题转换为一类线性矩阵不等式的可解问题.并且研究了模型误差与闭环系统稳定性之间的关系,给出了保证系统稳定条件下模型误差界的求取方法,通过求解一个线性矩阵不等式约束的凸优化问题得到保证闭环系统稳定的误差界.最后,利用算例对本文方法的有效性进行了验证.     

Delay‐dependent Stability and Static Output Feedback Control of 2‐D Discrete Systems with Interval Time‐varying Delays

This paper is concerned with the problems of delay‐dependent stability and static output feedback (SOF) control of two‐dimensional (2‐D) discrete systems with interval time‐varying delays, which are described by the Fornasini‐Marchesini (FM) second model. The upper and lower bounds of delays are considered. Applying a new method of estimating the upper bound on the difference of Lyapunov function that does not ignore any terms, a new delay‐dependent stability criteria based on linear matrix inequalities (LMIs) is derived. Then, given the lower bounds of time‐varying delays, the maximum upper bounds in the above LMIs are obtained through computing a convex optimization problem. Based on the stability criteria, the SOF control problem is formulated in terms of a bilinear matrix inequality (BMI). With the use of the slack variable technique, a sufficient LMI condition is proposed for the BMI. Moreover, the SOF gain can be solved by LMIs. Numerical examples show the effectiveness and advantages of our results.