关于时滞反馈控制的一般时滞Lur’e系统混沌同步的研究

采用M-矩阵方法和Lyapunov函数方法以及时滞反馈控制技术研究一般时滞Lur’e系统的混沌同步问题,得到易于检验的与时滞无关的代数判据,从而方便地设计出这种混沌同步方案的反馈控制器。最后,给出例子加以说明。     

具有输入饱和的非线性广义时滞系统的H∞控制

研究一类具有输入饱和的非线性广义时滞系统的H∞控制问题.使用线性矩阵不等式方法和Lyapunov稳定性理论给出该系统具有H∞范数约束γ的充分条件,并给出一种H∞控制器的设计方法.运用一个数值算例来说明本文方法的有效性.     

多胞型不确定时变时滞系统的H_∞滤波性能分析

对多胞型不确定时变时滞系统的H∞滤波性能进行分析,在此系统中,通过构造Lyapunov-Kra-sovkii函数,利用Schur补性质,得到基于线性矩阵不等式表示的H∞滤波器的设计方法,使得滤波误差动态系统是渐近稳定的并满足给定的H∞性能要求。从而将多胞型不确定时变时滞系统的H∞滤波器存在的充分条件归结为一个具有线性矩阵不等式约束的凸优化求解问题。     

Adaptive output feedback neural network control of uncertain non-affine systems with unknown control direction

This paper deals with the problem of adaptive output feedback neural network controller design for a SISO non-affine nonlinear system. Since in practice all system states are not available in output measurement, an observer is designed to estimate these states. In comparison with the existing approaches, the current method does not require any information about the sign of control gain. In order to handle the unknown sign of the control direction, the Nussbaum-type function is utilized. In order to approximate the unknown nonlinear function, neural network is firstly exploited, and then to compensate the approximation error and external disturbance a robustifying term is employed. The proposed controller is designed based on strict-positive-real (SPR) Lyapunov stability theory to ensure the asymptotic stability of the closed-loop system. Finally, two simulation studies are presented to demonstrate the effectiveness of the developed scheme.     

具有凸多面体不确定参数Delta算子时滞系统的可靠保性能控制

研究Delta算子描述的线性不确定时滞系统的可靠保性能控制问题。考虑系统含有具有凸多面体不确定性参数和连续模型执行器故障,根据Lyapunov稳定性理论,给出对于所有允许的不确定性和执行器故障．均使闭环系统渐近稳定且给定性能指标具有一定上界的状态反馈控制器的存在条件,由此提出相应控制器的设计方法。通过数值算例验证了设计方法的可行性。     

一类离散时滞随机系统的稳定性分析

针对一类不确定随机离散变时滞系统,建立了随机稳定性标准,该系统中随机干扰满足布朗运动。选取合适的李雅普诺夫函数,借助于随机稳定性理论、自由权矩阵和线性矩阵不等式等方法,给出并证明了使得该系统随机稳定的充分条件,所有结果以线性矩阵不等式的形式给出,应用例子和仿真表明所给稳定性标准的有效性。     

Delay-dependent robust control for uncertain discrete singular systems with time-varying delay

The design problem of delay-dependent robust control For uncertain discrete singular systems with time-varying delay is addressed in this paper. The uncertainty is assumed to be norm-bounded. By establishing a finite sum inequality based on quadratic terms, a new delay-dependent robust stability condition is derived and expressed in terms of linear matrix inequalities （LMIs）. A suitable robust state feedback control law is presented, which guarantees that the resultant closed-loop system is regular, causal and stable for all admissible uncertainties. Numerical examples are given to demonstrate the applicability of the proposed method.     

Optimal sizing of piezo-actuators for minimum-deflection design of frames under uncertain loads

Optimal piezo-actuator sizes and locations for a frame structure under bending load uncertainty are determined with the objective of minimizing the deflection under worst case of loading. The bending moments generated by the piezo-actuators are used for deflection control, i.e., to minimize the maximum deflection. The frame is subjected to a tip load which lies in an uncertainty domain with regard to its magnitude and direction. The specific uncertain loading studied in the present paper involves a load of given magnitude but of unknown direction, which should be determined to produce the highest deflection. The worst case of loading depends on the size and location of the actuators leading to a nested problem of optimization (design) and anti-optimization (uncertainty problem). Results are given for deterministic and uncertain loading conditions.     

具有时变不确定参数的线性时滞系统的鲁棒镇定

研究了具有时变不确定参数的线性时滞系统的鲁棒镇定问题．提出鲁棒稳定化控制器一种新的设计方法．现有的一些结果可以作为本文的一些特例得到．     

Optimal filtering over linear observations with unknown parameters

This paper presents the optimal filtering and parameter identification problem for linear stochastic systems over linear observations with unknown parameters, where the unknown parameters are considered Wiener processes. The original problem is reduced to the filtering problem for an extended state vector that incorporates parameters as additional states. The resulting filtering system is bilinear in state and linear in observations. The obtained optimal filter for the extended state vector also serves as the optimal identifier for the unknown parameters. Performance of the designed optimal state filter and parameter identifier is verified for both, positive and negative, parameter values.