基于类Lyapunov函数的非线性切换系统的Reach-While-Stay性质验证

考虑了一类连续时间切换系统在任意切换信号下的Reach-While-Stay性质验证问题,提出了基于类Lyapunov函数的验证方法.首先,利用不变集构建了新的RWS性质判定准则,将RWS性质验证问题转化为关于类Lyapunov函数的非线性约束求解问题,然后运用平方和松弛进行编码,进而将其转化为双线性矩阵不等式问题并应用迭代的半定规划进行求解.最后,通过实例表明了该方法的可行性和有效性.     

切换多项式非线性系统的输入-状态稳定性

利用耗散不等式研究了切换多项式非线性系统的输入-状态稳定性分析问题,在任意切换信号下,给出了使得切换多项式非线性系统输入-状态稳定的充分条件.采用平方和分解方法来寻找切换多项式非线性系统的输入-状态稳定共同Lyapunov函数.数值算例验证了所提方法的可行性.     

具有承袭性的高阶导数有理插值算法

切触有理插值是函数逼近的一个重要内容,而降低切触有理插值的次数和解决切触有理插值函数的存在性是有理插值的一个重要问题.切触有理插值函数的算法大都是基于连分式进行的,其算法可行性是有条件的,且计算量较大.利用Newton(牛顿)多项式插值的承袭性和分段组合的方法,构造出了一种无极点且满足高阶导数插值条件的切触有理插值函数,并推广到向量值切触有理插值情形;既解决了切触有理插值函数存在性问题,又降低了切触有理插值函数的次数.最后给出误差估计,并通过数值实例说明该算法具有承袭性、计算量低、便于编程等特点.     

矩形网格上的二元切触有理插值

二元切触有理插值是有理插值的一个重要内容,而降低其函数的次数和解决其函数的存在性是有理插值的一个重要问题.二元切触有理插值算法的可行性大都是有条件的,且计算复杂度较大,有理函数的次数较高.利用二元Hermite（埃米特）插值基函数的方法和二元多项式插值误差性质,构造出了一种二元切触有理插值算法并将其推广到向量值情形.较之其它算法,有理插值函数的次数和计算量较低.最后通过数值实例说明该算法的可行性是无条件的,且计算量低.     

Stieltjes-Newton型有理插值

Stieltjes型分叉连分式在有理插值问题中有着重要的地位，它通过定义反差商和混合反差商构造给定结点上的二元有理函数，我们将Stieltjes型分叉连分式与二元多项式结合起来，构造Stieltje- Newton型有理插值函数，通过定义差商和混合反差商，建立递推算法，构造的Stieltjes-Newton型有理插值函数满足有理插值问题中所给的插值条件，并给出了插值的特征定理及其证明，最后给出的数值例子，验证了所给算法的有效性．     

0-1多项式规划问题的SDP松弛方法(英)

本文提出了一类新的构造0-1多项式规划的半定规划(SDP)松弛方法. 我们首先利用矩阵分解和分片线性逼近给出一种新的SDP松弛, 该 松弛产生的界比标准线性松弛产生的界更紧. 我们还利用 拉格朗日松弛和平方和(SOS)松弛方法给出了一种构造Lasserre的SDP 松弛的新方法.     

有理反插值

在解决反插值问题时,本文首次利用Thiele型连分式有理插值,得到了两种十分有效的方法:函数插值的有理反插法和反函数的有理插值法,同多项式反插值相比有较好的效果.数值例子说明了在解代数方程时有理反插法优于多项式反插法.     

切触有理插值新方法

针对传统连分式插值,计算复杂度高,计算过程中分母为零的不可预知性及插值函数不满足某些给定条件,应用不方便等问题,利用已知节点、函数值、导数值,构造两个多项式,分别作为有理插值函数的分子和分母,得出各阶导数条件下切触有理插值的新公式,并给出特殊情形的表达式.若添加适当的参数,可任意降低插值函数次数.该方法计算简洁,应用方便,插值函数的分母在节点处不为零且满足全部插值条件.数值例子验证了新方法的可行性、有效性和实用性.     

基于拟Legendre多项式求解一类分数阶微分方程

本文基于移位的Legendre多项式构造一类新的正交拟Legendre多项式求解一类分数阶微分方程.用阶数随所求未知函数的微分的阶数而变化的拟Legendre多项式逼近未知函数;利用分数阶积分的性质推导拟Legendre多项式的积分算子阵,结合算子矩阵的思想和Tau方法,将问题转化为求解代数方程组的问题.最后,给出数值算例证明该方法的有效性.     

有理线性插值曲线和曲面

构造了含参数的分段线性有理插值函数(分子、分母均为一次多项式),通过适当选择形状参数,由此函数产生的曲线一阶连续并且保单调.文中用张量积方法将此结果推广到二元矩形网格上的曲面插值,同时给出了插值函数的误差估计及数值例子.     

Control vector Lyapunov functions for large-scale impulsive dynamical systems

Vector Lyapunov theory has been developed to weaken the hypothesis of standard Lyapunov theory in order to enlarge the class of Lyapunov functions that can be used for analyzing system stability. In this paper, we provide generalizations to the recent extensions of vector Lyapunov theory for continuous-time systems to address stability and control design of impulsive dynamical systems via vector Lyapunov functions. Specifically, we provide a generalized comparison principle involving hybrid comparison dynamics that are dependent on the comparison system states as well as the nonlinear impulsive dynamical system states. Furthermore, we develop stability results for impulsive dynamical systems that involve vector Lyapunov functions and hybrid comparison inequalities. Based on these results, we show that partial stability for state-dependent impulsive dynamical systems can be addressed via vector Lyapunov functions. Furthermore, we extend the recently developed notion of control vector Lyapunov functions to impulsive dynamical systems. Using control vector Lyapunov functions, we construct a universal hybrid decentralized feedback stabilizer for a decentralized affine in the control nonlinear impulsive dynamical system that possesses guaranteed gain and sector margins in each decentralized input channel. These results are then used to develop hybrid decentralized controllers for large-scale impulsive dynamical systems with robustness guarantees against full modeling and input uncertainty.     

BiCR variants of the hybrid BiCG methods for solving linear systems with nonsymmetric matrices

We propose Bi-Conjugate Residual (BiCR) variants of the hybrid Bi-Conjugate Gradient (BiCG) methods (referred to as the hybrid BiCR variants) for solving linear systems with nonsymmetric coefficient matrices. The recurrence formulas used to update an approximation and a residual vector are the same as those used in the corresponding hybrid BiCG method, but the recurrence coefficients are different; they are determined so as to compute the coefficients of the residual polynomial of BiCR. From our experience it appears that the hybrid BiCR variants often converge faster than their BiCG counterpart. Numerical experiments show that our proposed hybrid BiCR variants are more effective and less affected by rounding errors. The factor in the loss of convergence speed is analyzed to clarify the difference of the convergence between our proposed hybrid BiCR variants and the hybrid BiCG methods.     

Automatically Discovering Relaxed Lyapunov Functions for Polynomial Dynamical Systems

The notion of Lyapunov function plays a key role in the design and verification of dynamical systems, as well as hybrid and cyber-physical systems. In this paper, to analyze the asymptotic stability of a dynamical system, we generalize standard Lyapunov functions to relaxed Lyapunov functions (RLFs), by considering higher order Lie derivatives. Furthermore, we present a method for automatically discovering polynomial RLFs for polynomial dynamical systems (PDSs). Our method is relatively complete in the sense that it is able to discover all polynomial RLFs with a given predefined template for any PDS. Therefore it can also generate all polynomial RLFs for the PDS by enumerating all polynomial templates.     

Stability analysis of polynomial fuzzy models via polynomial fuzzy Lyapunov functions

In this paper, the stability of continuous-time polynomial fuzzy models by means of a polynomial generalization of fuzzy Lyapunov functions is studied. Fuzzy Lyapunov functions have been fruitfully used in the literature for local analysis of Takagi-Sugeno models, a particular class of the polynomial fuzzy ones. Based on a recent Taylor-series approach which allows a polynomial fuzzy model to exactly represent a nonlinear model in a compact set of the state space, it is shown that a refinement of the polynomial Lyapunov function so as to make it share the fuzzy structure of the model proves advantageous. Conditions thus obtained are tested via available SOS software.     

Volterra series approximation for rational nonlinear system

Rational nonlinear systems are widely used to model the phenomena in mechanics, biology, physics and engineering. However, there are no exact analytical solutions for rational nonlinear system. Hence, the approximate analytical solutions are good choices as they can give the estimation of the states for system analysis, controller design and reduction. In this paper, an approximate analytical solution for rational nonlinear system is derived in terms of the solution of a polynomial system by Volterra series theory. The rational nonlinear system is transformed to a singular polynomial system with finite terms by adding some algebraic constraints related to the rational terms. The analytical solution of singular polynomial system is approximated by the summation of the solutions of Volterra singular subsystems. Their analytical solutions are derived by a novel regularization algorithm. The first fourth Volterra subsystems are enough to approximate the analytical solution to guarantee the accuracy. Results of numerical experiments are reported to show the effectiveness of the proposed method.     

A unified approach to one-parametric general quadratic programming

A method is proposed for finding local minima to the parametric general quadratic programming problem where all the coefficients are linear or polynomial functions of a scalar parameter. The local minimum vector and the local minimum value are determined explicitly as rational functions of the parameter. A numerical example is given.     

A novel approach for the computation of orthonormal polynomial expansions

In this paper we present a novel technique for the computation of orthonormal polynomial expansions. The proposed method is very straightforward; given a function to be expanded in a polynomial series, we first use the FFT to compute a vector of Fourier coefficients. Then, using a change of basis transformation, we go from the Fourier coefficients to the polynomial coefficients. Convergence properties for this new approach are investigated.     

有理曲线的多项式逼近

利用曲线摄动的思想给出了用多项式曲线逼近有理曲线的一种新方法．其基本步骤是对有理曲线的控制顶点进行摄动，使之产生一多项式曲线，并使摄动误差在某种范数意义之下达到最小．同时，通过适当控制摄动曲线的顶点，使逼近多项式曲线与有理曲线在两端点保持一定的连续性．这一结果可以与细分（ｓｕｂｄｉｖｉｓｉｏｎ）技术结合给出有理曲线的整体光滑的分片多项式逼近．实例表明，在某些情况下本文中的方法要优于传统的Ｈｅｒｍｉｔｅ插值方法及Ｔ．Ｗ．Ｓｅｄｅｒｂｅｒｇ和Ｍ．Ｋａｋｉｍｏｔｏ（１９９１）提出的杂交曲线逼近算法．     

An SOS-QE Approach to Nonlinear Gain Analysis for Polynomial Dynamical Systems

Combined use of the method of sum of squares (SOS) and quantifier elimination (QE) is discussed with regard to the problem of nonlinear gain analysis for a class of dynamical systems. SOS, a numerical method, is used to search for the structure of a gain function quickly, and QE, a symbolic method, determines all gain functions in the structure to find the minimum gain function. QE can also be used for the infeasibility check of gain structures. A proposed analysis procedure for polynomial dynamical systems prevents unnecessary searching for a gain structure. Two illustrative examples show the effectiveness of the proposed gain analysis procedure.