浅谈解的存在唯一性定理在《偏微分方程数值解》中的应用

从一个新的角度讨论常微分方程中解的存在唯一性定理在偏微分方程数值解法中的重要应用。给出一类伪双曲型偏微分方程的新的分裂混合有限元数值格式,将该格式转化成常微分方程系统,利用解的存在唯一性定理证明该系统是存在唯一解的。通过简短的讨论、概述明确解的存在唯一定理在偏微分方程数值解中的应用方法．并希望能够在教学科研未来的发展中有新的观念。     

一类广义非线性系统的无源控制

考虑一类广义非线性系统的无源控制问题，利用广义Lyapunov函数和线性矩阵不等式，给出广义非线性系统无源且零解渐近稳定的充分条件。并在一定条件下得到存在状态反馈无源控制器，使得闭环系统无源且零解渐近稳定的充分条件，同时给出相应的控制器构造方法。     

正倒向随机微分方程与一类线性二次随机最优控制问题

讨论一类正倒向随机微分方程解的存在唯一性及其对应的一类线性二次随机最优控制 问题,利用单调性方法证明了一类特殊的正倒向随机微分方程解的存在唯一性定理,利用该结果 研究一类耦合了一个倒向随机微分方程的线性随机控制系统广义最优指标随机控制问题,得到 由正倒向随机微分方程的解所表示的唯一最优控制的显式表达式,并得到精确的线性反馈及其 对应的Riccati方程.     

自治混沌系统普适广义投影同步理论及应用

针对自治混沌系统，基于系统稳定性理论，通过设计合适的非线性反馈控制器，给出了普适的广义投影同步定理．定理中函数的选择可以为系统的线性或非线性函数，更具灵活性和普适性；文中理论还可以通过调整参数提高广义投影同步的速度．数值仿真进一步验证了本文理论的有效性和实用性．     

非线性系统零解稳定性判定的广义二次型方法

为了寻找一种能充分利用矩阵理论构造非线性系统李亚普诺夫函数的方法．首先提出分量函数矩阵和广义二次型函数等概念，得到了如果一个函数的导数具有某种特定形式。则不需处理旋度方程．便可直接得到该函数的若干定理；然后提出一种构造李亚普诺夫函数和判定非线性系统零解稳定性的广义二次型方法．并举例说明了该方法的应用．理论和实例表明，该方法是一种充分利用矩阵特性，适用范围广且不需处理旋度方程的方法．     

连续广义系统多点边值问题解的结构

本文在多点边值的约束条件下，讨论了连续广义控制系统解的存在唯一性及解的结构。并用Ｇｒｅｅｎ函数给出了解的表达式。     

广义非线性系统的变结构控制理论

利用几何方法,从广义非线性系统本身出发,研究了广义非线性控制的变化结构控制理论,给出了系统存在变结构控制的充分实际没动模式的近似定理。从所得结论可知,滑动条件仅能保证实际滑动模的慢变状态赵近于理想滑动模的慢变状态,而不能保证实际滑动模的状态趋近于理想滑动模的快变状态,研究正常非线性系统的方法已不能简单地被利用到广义非线性系统。     

广义系统的周期解

本文研究了几类广义系统，得出了一类广义线性非齐次系统存在周期解的充要条件，一类广义线性时变系统存在唯一周期解的充分条件；一类广义非线性系统存在周期解的充分条件。     

T-S模糊广义系统的逼近性

本文研究T-S模糊广义系统的逼近性,给出了T-S模糊广义系统的逼近性定理.证明其可以以任意的精度逼近一类广泛存在的非线性广义系统.还将MISO(多输入单输出)情况推广到MIMO(多输入多输出)的情况.在逼近性定理的基础上,利用神经网络的方法对非线性广义系统建模,给出了神经网络的结构及学习算法.本文共提出了两种神经网路的训练策略,对各自的优点与不足给出了分析,最后用数值例子验证了算法的有效性.     

具有空间扩散和尺度结构的非线性害鼠模型的最优不育控制

本文讨论了一类具有尺度结构的非线性时变害鼠扩散模型的适定性及最优不育控制问题. 状态系统由二阶偏微分–积分方程描述, 此系统有一种重要的特殊情形, 即死亡率分为自然死亡率和额外死亡率, 系统的解关于尺度和空间位置可分离, 从而将系统分为两个子系统, 利用比较原则和不动点定理证明了变量分离型解的存在唯一性和非负有界性. 本文运用Mazur定理证明了最优策略的存在性, 导出共轭系统并借助凸集的切锥–法锥技巧给出了最优策略的必要性条件, 为模型的实际应用奠定了理论基础. 最后, 采用向后差分格式和追赶法分别对子系统的解进行了数值模拟.     

Stabilizing feedbacks for imperfectly known,singularly perturbed nonlinear systems with discrete and distributed delays

A class of nonlinear memoryless controllers is synthesized to guarantee global uniform ultimate boundedness, with respect to some known set, for a class of imperfectly known singularly perturbed nonlinear systems, with discrete and distributed delays, provided that the singular perturbation parameter is small enough. Each feedback controller is designed using information based mainly on a nonlinear, affine in the control, ‘reduced-order’ system. The uncertainty, which may be time, state, delayed state and/or input dependent, is modelled by additive nonlinear perturbations influencing a known nominal, singularly perturbed time-delay system of the retarded type. A ‘matched’ uncertainty structural condition for the reduced-order system is not presumed in this paper.     

A ROBUST ADAPTIVE CONTROL DESIGN FOR A CLASS OF UNCERTAIN NONLINEAR MARKOVIAN JUMP SYSTEMS

A direct robust adaptive nonlinear control scheme for a class of uncertain nonlinear Markovian jump systems with nonlinear state‐dependent uncertainty is presented. The proposed scheme is Lyapunov‐based and guarantees the global uniform ultimate boundedness of the closed‐loop system in the mean sense. A numerical example is given to demonstrate the validity of the results.     

The nonlinear Volterra equation of Abel's kind and its numerical treatment

Starting from an existence and uniqueness theorem for a generalized nonsingular second kind Volterra equation existence and uniqueness for the solution of the nonlinear, weakly singular first kind Volterra equation is examined. A new type of numerical method is developed. A basic lemma concerning the boundedness of a special difference inequality is given and order two or three convergence of the method is shown. Two numerical examples illustrate the theoretical results.     

Robust adaptive control for interval time-delay systems

1 Introduction The problem of time-delay is commonly encountered in various engineering systems, such as electric, pneumatic and hydraulic networks, long transmission lines, etc., and it is also a great source of systems instability and poor perfor- mance. During the last decades, we have seen an increasing interest for the control of this class of systems and many results have reported in the literature [1～5]. On the other hand, it has been recognized that nonlinear uncertainties are unavoid…     

一类不确定非线性系统的自适应支持向量回归建模与动态面控制

针对一类非线性严格反馈系统,提出一种基于自适应支持向量回归的动态面控制方法.首先,将支持向量回归的核函数在核宽度以及支持向量估计值处进行一阶泰勒展开,使其能够对核宽度和支持向量进行线性化表示;然后,利用支持向量回归对系统未知动态建模,并基于建模结果设计虚拟控制器和控制器,同时,为提高建模精度,在控制器设计中增加系统状态及其跟踪误差的预测变量,并根据预测误差设计参数自适应律;最后,基于李雅普诺夫定理给出系统一致最终有界的分析.仿真结果表明,所提出的方法能有效减小建模误差并提高跟踪精度.     

Adaptive NN control of uncertain nonlinear pure-feedback systems

This paper is concerned with the control of nonlinear pure-feedback systems with unknown nonlinear functions. This problem is considered difficult to be dealt with in the control literature, mainly because that the triangular structure of pure-feedback systems has no affine appearance of the variables to be used as virtual controls. To overcome this difficulty, implicit function theorem is firstly exploited to assert the existence of the continuous desired virtual controls. NN approximators are then used to approximate the continuous desired virtual controls and desired practical control. With mild assumptions on the partial derivatives of the unknown functions, the developed adaptive NN control schemes achieve semi-global uniform ultimate boundedness of all the signals in the closed-loop. The control performance of the closed-loop system is guaranteed by suitably choosing the design parameters.     

基于神经网络的非线性连续系统的自适应调节器

对于一类连续时间的非线性动态系统x=f(x)+Bu+d,当系统中的非线性函数f(x)满足线性增长条件时,首先证明了f(x)中的x落入一紧集中,然后根据神经网络的逼近性质,给出了自适应调节器的设计方法.利用李雅普诺夫稳定性理论,证明了控制算法是全局稳定的,闭环系统的状态是一致最终有界的.     

Uniformly ultimately bounded fuzzy adaptive tracking controllers for uncertain systems

Fuzzy adaptive tracking controllers for a class of uncertain nonlinear dynamical systems are proposed and analyzed. The controllers consist of adaptive and robustifying components whose role is to ify the effects of uncertainties and to achieve a desired tracking performance. The interactions between the two components have been investigated. The closed-loop system driven by the proposed controllers is shown to be stable with all the adaptation parameters being bounded. In particular, the proposed controllers guarantee uniform ultimate boundedness of the tracking error and the time bound of the uniform ultimate boundedness is obtained. An upper bound on the steady-state tracking error is obtained as a function of the gain of the robustifying term and the parameters of the adaptive component. The controllers are tested on an inverted pendulum and simulation results are included. A comparison of the proposed controllers with the ones in the literature is conducted.     

Adaptive fuzzy robust tracking controller design via small gain approach and its application

An adaptive fuzzy robust tracking control (AFRTC) algorithm is proposed for a class of nonlinear systems with the uncertain system function and uncertain gain function, which are all the unstructured (or nonrepeatable) state-dependent unknown nonlinear functions arising from modeling errors and external disturbances. The Takagi-Sugeno type fuzzy logic systems are used to approximate unknown uncertain functions and the AFRTC algorithm is designed by use of the input-to-state stability approach and small gain theorem. The algorithm is highlighted by three advantages: 1) the uniform ultimate boundedness of the closed-loop adaptive systems in the presence of nonrepeatable uncertainties can be guaranteed; 2) the possible controller singularity problem in some of the existing adaptive control schemes met with feedback linearization techniques can be removed; and 3) the adaptive mechanism with minimal learning parameterizations can be obtained. The performance and limitations of the proposed method are discussed. The uses of the AFRTC for the tracking control design of a pole-balancing robot system and a ship autopilot system to maintain the ship on a predetermined heading are demonstrated through two numerical examples. Simulation results show the effectiveness of the control scheme.     

Ultimate boundedness control of linear systems with band-bounded nonlinear actuators and additive measurement noise

For linear systems driven by band-bounded nonlinear actuators, a set of linear matrix inequality (LMI) based sufficient conditions are derived for finding state feedback controllers which assure ultimate boundedness of state trajectories. Besides actuator nonlinearity, it is assumed that additive noise exists when state variables are measured for feedback. The purpose is to minimize the ultimate boundedness region while tolerating noise of the largest magnitude. When a state feedback controller is determined for a given system by solving the LMI conditions or by any other means, a less conservative LMI condition is given for further examination of the resultant ultimate boundedness region and tolerable noise magnitude.