Linear matrix inequality approach to exponential synchronization of a class of chaotic neural networks with time-varying delays

In this paper, a synchronization scheme for a class of chaotic neural networks with time-varying delays is presented. This class of chaotic neural networks covers several well-known neural networks, such as Hopfield neural networks, cellular neural networks, and bidirectional associative memory networks. The obtained criteria are expressed in terms of linear matrix inequalities, thus they can be efficiently verified. A comparison between our results and the previous results shows that our results are less restrictive.

On stabilization for a class of nonlinear stochastic time-delay systems:a matrix inequality approach

This paper treats the feedback stabilization of nonlinear stochastic time-delay systems with state and control-dependent noise. Some locally （globally） robustly stabilizable conditions are given in terms of matrix inequalities that are independent of the delay size. When it is applied to linear stochastic time-delay systems, sufficient conditions for the state-feedback stabilization are presented via linear matrix inequalities. Several previous results are extended to more general systems with both state and control-dependent noise, and easy computation algorithms are also given.

Linear matrix inequality approach for synchronization control of fuzzy cellular neural networks with mixed time delays

Fuzzy cellular neural networks （FCNNs） are special kinds of cellular neural networks （CNNs）. Each cell in an FCNN contains fuzzy operating abilities. The entire network is governed by cellular computing laws. The design of FCNNs is based on fuzzy local rules. In this paper, a linear matrix inequality （LMI） approach for synchronization control of FCNNs with mixed delays is investigated. Mixed delays include discrete time-varying delays and unbounded distributed delays. A dynamic control scheme is proposed to achieve the synchronization between a drive network and a response network. By constructing the Lyapunov-Krasovskii functional which contains a triple-integral term and the free-weighting matrices method an improved delay-dependent stability criterion is derived in terms of LMIs. The controller can be easily obtained by solving the derived LMIs. A numerical example and its simulations are presented to illustrate the effectiveness of the proposed method.

Linear matrix inequality approach for robust stability analysis for stochastic neural networks with time-varying delay

This paper studies the problem of linear matrix inequality （LMI） approach to robust stability analysis for stochastic neural networks with a time-varying delay. By developing a delay decomposition approach, the information of the delayed plant states can be taken into full consideration. Based on the new Lyapunov-Krasovskii functional, some inequality techniques and stochastic stability theory, new delay-dependent stability criteria are obtained in terms of LMIs. The proposed results prove the less conservatism, which are realized by choosing new Lyapunov matrices in the decomposed integral intervals. Finally, numerical examples are provided to demonstrate the less conservatism and effectiveness of the proposed LMI method.

Generalizations of a Matrix Inequality

In this paper, some new generalizations of the matrix form of the Brunn-Minkowski inequality are presented.

The Generalization of a Converse of Matrix Inequality

We prove that the inequality holds, when a m × n real matrix X = (xij) whose entries are not all equal to 0 satisfies Therefore we not only generalize the results of Horst Alzer [2] from non-negative matrix to real matrix, but also complete a result of E R van Dam [1], which indicated that the best possible upper bound is equal to 1 for real matrix.

A Matrix Inequality for the Inversions of the Restrictions of a Positive Definite Hermitian Matrix

We exploit the theory of reproducing kernels to deduce a matrix inequality for the inverse of the restriction of a positive definite Hermitian matrix.

Global stabilization of linear periodically time-varying switched systems via matrix inequalities

In this paper, we address the stabilization problem for linear periodically time-varying switched systems. Using discretization technique, we derive new conditions for the global stabilizability in terms of the solution of matrix inequalities. An algorithm for finding stabilizing controller and switching strategy is presented.

On absolute stability of Lur'e control systems with multiple non-linearities using linear matrix inequalities

Necessary and suffcient conditions for the existence of a Lyapunov function in the Lur ’ e form to guarantee the absolute stability of Lur’ e control systems with multiple non-linearities are discussed in this paper. It simplifies the existence problem to one of solving a set of linear matrix inequalities (LMIs). If those LMIs are feasible, free parameters in the Lyapunov function, such as the positive definite matrix and the coefficients of the integral terms, are given by the solution of the LMIs. Otherwise, this Lyapunov function does not exist. Some sufficient conditions are also obtained for the robust absolute stability of uncertain systems. A numerical example is provided to demonstrate the effectiveness of the proposed method.

Several Generalized Matrix Versions of Kantorovich Inequalities

Kantorovich inequalities are old results. In this paper we give several Kantorovich-type matrix inequalities.

THE OPPENHEIM-TYPE INEQUALITIES FORTHE HADAMARD PRODUCT OF M-MATRIXAND POSITIVE DEFINITE MATRIX

For the lower bound about the determinant of Hadamard product of A and B, where A is a n × n real positive definite matrix and B is a n × n M-matrix, Jianzhou Liu [SLAM J. Matrix Anal. Appl., 18(2)(1997): 305-311]obtained the estimated inequality as follows det(A o B)≥a11b11 nⅡk=2(bkk detAk/detAk-1+detBk/detBk-1(k-1Ei=1 aikaki/aii))=Ln(A,B),where Ak is kth order sequential principal sub-matrix of A. We establish an improved lower bound of the form Yn(A,B)=a11baa nⅡk=2(bkk detAk/detAk-1+akk detBk/detBk-1-detAdetBk/detak-1detBk-1)≥Ln(A,B).For more weaker and practical lower bound, Liu given thatdet(A o B)≥(nⅡi=1 bii)detA+(nⅡi=1 aii)detB(nⅡk=2 k-1Ei=1 aikaki/aiiakk)=(L)n(A,B).We further improve it as Yn(A,B)=(nⅡi=1 bii)detA+(nⅡi=1 aii)detB-(detA)(detB)+max1≤k≤n wn(A,B,k)≥(nⅡi=1 bii)detA+(nⅡi=1 aii)detB-(detA)(detB)≥(L)n(A,B).

Hermite Positive Definite Solution of the Quaternion Matrix Equation Xm + B*XB = C

This paper discusses the necessary and sufficient conditions for the existence of Hermite positive definite solutions of the quaternion matrix equation Xm+ B*XB = C (m > 0) and its iterative solution method. According to the characteristics of the coefficient matrix, a corresponding algebraic equation system is ingeniously constructed, and by discussing the equation system’s solvability, the matrix equation’s existence interval is obtained. Based on the characteristics of the coefficient matrix, some necessary and sufficient conditions for the existence of Hermitian positive definite solutions of the matrix equation are derived. Then, the upper and lower bounds of the positive actual solutions are estimated by using matrix inequalities. Four iteration formats are constructed according to the given conditions and existence intervals, and their convergence is proven. The selection method for the initial matrix is also provided. Finally, using the complexification operator of quaternion matrices, an equivalent iteration on the complex field is established to solve the equation in the Matlab environment. Two numerical examples are used to test the effectiveness and feasibility of the given method. .

一种含扰动非线性离散系统的故障观测器设计方法

针对一类含扰动、传感器故障和执行器故障的非线性离散系统,提出了一种新型的故障观测器设计方法,该方法既考虑到了故障的类型,又考虑到了故障估计误差的收敛速度,故障估计方法适用性更强。首先,构造出含系统状态和传感器故障的增广向量,得到一个等价的广义系统;其次,考虑到系统中的执行器故障及故障估计的速度,构建同时含系统状态、执行器故障和传感器故障的故障观测器,并给出故障观测器存在的充分条件;最后,通过某飞机的纵向运动系统等非线性离散系统模型,对增广状态向量进行鲁棒估计,故障估计结果验证了该方法的优越性。

一种含扰动离散非线性系统状态观测器的设计方法

针对一类含扰动的非线性离散系统,讨论了系统状态观测器的设计问题,给出了一种离散系统状态观测器的设计方法,并将该方法应用到奇异系统观测器设计中。首先,根据李雅普诺夫稳定性理论,得到离散系统在不含外部扰动下观测器增益矩阵存在的充分条件;其次,考虑到离散系统的扰动项,针对系统中的外部扰动在李雅普诺夫函数设计中纳入性能指标,得到含扰动情况下离散系统观测器增益矩阵存在的充分条件,该方法可以通过设置性能指标减弱扰动对系统状态估计的影响,同时也有利于增益矩阵的设计与求解;最后,将非线性离散系统观测器的设计方法推广到奇异系统中,从而使该方法更具一般性。利用三个数值算例对所提方法进行了检验,仿真结果表明了文中所提方法的可行性与有效性。

非线性广义时滞Markov跳变系统的H_(∞)滑模控制

研究了一类转移速率部分未知的广义时滞Markov跳变系统的H_(∞)滑模控制问题.首先,对广义时滞Markov跳变系统设计了积分型滑模面,并求出对应的等效控制器.之后,构建Lyapunov泛函,通过线性矩阵不等式方法得到闭环系统随机容许且满足H_(∞)性能γ的充分条件,运用加减项方法以及引入自由权矩阵,使得到的结果降低了保守性;对滑模力学分析,设计了滑模控制器,使得系统能在有限时间内到达滑模面上.最后,通过数值算例与仿真验证了理论的可行性.

一类具有非线性扰动的分布式中立系统的稳定性判据

针对一类具有非线性扰动的分布式中立系统,设计了状态反馈控制器.根据李雅普诺夫稳定性理论,结合自由加权矩阵及牛顿-莱布尼茨公式对系统进行稳定性分析,并利用线性矩阵不等式给出系统的稳定性判据.数值仿真进一步验证了所提控制方法的有效性.

具有H_(∞)性能的输入受限三级倒立摆控制器设计

【目的】针对直线三级倒立摆控制输入受限下的稳摆控制问题,设计了具有H_(∞)性能的输入受限三级倒立摆控制器。【方法】利用线性矩阵不等式(LMI)方法,将控制输入约束问题转化为利用线性矩阵不等式求解优化值的优化问题,经Lyapunov稳定性推导出符合条件的LMI,利用MATLAB中的LMI工具箱求解得到有效的K。进一步在控制输入受限下引入H_(∞)性能指标,使所设计的控制输入受限下的算法具有H_(∞)性能。【结果】仿真结果表明,该控制器对于控制输入受限下的复杂高阶次不稳定系统具有很好的控制效果。【结论】控制输入信号在给定的受限范围内实现了三级倒立摆的稳摆要求,且引入H_(∞)性能指标后控制输入和摆杆波动更小。

基于LMI和扰动观测器的电动伺服系统RBF神经网络控制

为了提高电动伺服系统的加载力跟踪精度,基于线性矩阵不等式(LMI)设计扰动观测器和控制器。针对系统中的非线性因素,采用RBF神经网络逼近系统的数学模型;在建立系统跟踪目标模型的基础上,根据LMI设计扰动观测器对控制器进行多余力的补偿,利用李雅普诺夫函数证明扰动观测器和控制器的收敛;在MATLAB/Simulink中搭建仿真模型,分析扰动观测器和RBF神经网络在不同工况下对系统相应量的精准估计,且误差均满足所设定的性能指标,同时与PID控制相比较,证明所提控制策略的控制性能更优。

执行器随机失效系统鲁棒预测容错切换控制

针对一类具有执行器随机失效问题的离散线性系统,提出一种基于故障概率情况下的鲁棒预测容错切换控制方法。首先,将工业过程建立成新型多自由度状态空间模型,设计含有故障概率的容错控制器;其次,引入系统故障和其恢复时的随机概率,利用李雅普诺夫判据给出基于线性矩阵不等式形式的稳定性条件,再通过指数稳定的相关证明求解出不同执行器切换时的稳定条件,以保证系统故障时容错控制与无故障时常规控制间的切换;然后,控制器设计时还充分考虑了设定值变化时所产生的跟踪误差带来的影响。最后,通过仿真结果验证了所提方法的可行性。

低轨多星编队的相对运动差分气动控制

针对低轨纳卫星轨道机动能力不足的问题,本文研究了主动利用星间差分气动力的控制方法,创新性地提出了基于迎风姿态调整的多星编队拓展方案,并通过局部区域线性化方法实现系统的线性控制.本文研究了卫星姿态角与气动力的映射关系,建立了差分阻力和升力耦合控制的星间相对运动线性欠驱动模型,分析了此系统可控性和干扰形式,采用线性矩阵不等式(LMI)方法设计了考虑输入受限的反馈控制律.最后,针对包含两种队形的四星编队进行仿真,结果表明,卫星相对运动的稳定控制精度达到±0.4m,验证了所提出多星编队气动控制方案的可行性以及控制算法的有效性.