一类不确定非线性时滞系统的模糊自适应控制

针对一类不确定上界未知的非线性时滞系统,基于松散稳定性条件,讨论了系统的模糊自适应控制问题 .通过在Lyapunov泛函中引入参数,得到带调节因子的时滞相关稳定性条件.设计出基于观测器的自适应模糊控制器,观测增益矩阵和反馈增益矩阵可以通过求解线性矩阵不等式得到 .当调节因子取不同值时,观测增益矩阵和反馈增益矩阵也是不同的,因此,闭环系统的动态性能可以通过选取合适的调节因子来优化.最后通过一个实例验证了所给结论的有效性.     

模糊输入时滞系统的输出反馈控制及稳定性分析

针对一类状态不可测的模糊输入时滞系统,应用平行分布补偿算法(PDC),设计了模糊观测器,提出了基于模糊观测器的输出反馈控制方法,给出了保证模糊时滞系统渐近稳定的新的充分条件.应用广义Lyapunov函数和线性矩阵不等式方法,证明了模糊输入时滞系统的渐近稳定性,同时给出了控制和观测增益矩阵的分离设计算法.仿真结果进一步验证了所提出的方法和条件的有效性.     

基于状态观测器的不确定时滞系统H_∞鲁棒容错控制

针对一类具有状态时滞的不确定线性系统,详细阐述了该系统基于状态观测器的H_∞鲁棒容错控制问题.当系统状态不可测时,构造状态观测器,并考虑状态观测器反馈回路传感器失效,引入观测误差,通过构造闭环增广系统的Lyapunov泛函,设计出了有容错性能的状态观测器和基于该观测器的状态反馈控制器,使得闭环增广系统渐近稳定,并满足H_∞性能指标.通过求解一个线性矩阵不等式就可同时得到观测器增益和控制器增益矩阵.最后给出仿真算例,验证了此方法的有效性.     

模糊时滞系统的输出反馈控制器设计

利用模糊T-S模型对一类非线性时滞系统进行建模;在此基础上,设计出了模糊静态输出反馈控制器和模糊动态输出反馈控制器,并利用Lyapunov-Razumikhin引理和线性矩阵不等式证明了系统渐近稳定的充分条件,通过求解一系列线性矩阵不等式,得到了反馈增益矩阵。     

基于观测器的模糊时滞系统的指数稳定控制

研究一类模糊时滞系统的指数稳定和基于观测器的模糊控制问题.在系统状态未知的情况下,通过设计系统的模糊观测器利用矩阵不等式分析的方法给出了系统指数稳定条件和基于观测器的动态输出反馈控制器设计方案.仿真结果说明了所提方法的有效性.     

具有数据丢失的网络化控制系统的基于观测器的镇定

研究具有数据丢失的网络化控制系统的基于观测器的镇定问题。受控对象是由T-S模糊模型描述的非线性时滞系统。把数据丢失过程建模成独立同分布过程。利用模糊Lyapunov函数方法得到了闭环系统随机稳定的充分条件,其基于观测器的反馈控制器可通过求解一组线性矩阵不等式来设计。一个仿真例子说明方法的有效性。     

具时滞反馈金融系统的动力学分析与混沌控制

研究了时滞反馈对金融系统的动力学行为的影响.以时滞为分支参数,研究了系统平衡点的局部稳定性,并发现当时滞经过一系列临界值时,系统在平衡点附近经历Hopf分支和Hopf-zero分支.然后,应用规范型方法和中心流形理论得到决定分支周期解性质的详细公式.通过设计合适的反馈增益和时滞,混沌振荡可以控制为稳定的平衡点或周期轨.最后,数值模拟验证了理论结果.     

一类不确定非线性系统的适应H-infinity控制

主要讨论了一类具有不确定参数的非线性系统的通过适应输出反馈达到干扰衰减的问题．通过构造降维观测器,利用Backstepping方法设计输出反馈控制器,使闭环系统具有不确定参数的标准的增益问题可解,并使系统达到内稳定．     

一类时滞Lipschitz非线性离散广义系统观测器的设计

针对一类时滞Lipschitz非线性离散广义系统,主要研究了系统的观测器设计问题.首先,基于广义系统的特殊结构对时滞广义系统进行变换,将系统转化为易于求取观测器的形式;其次,考虑到系统中的Lipschitz非线性项,将系统分两种情况并分别设计出了系统的观测器;最后,为保证系统与观测器的误差系统渐近稳定,通过利用线性矩阵不等式(LMI)的方法给出了两个观测器存在的条件,并通过数值例子验证了观测器设计方法的有效性.     

一类随机非线性马尔可夫切换系统的输出反馈控制

研究了一类具有马尔可夫切换的随机非线性系统的输出反馈镇定问题.利用非线性增益观测器设计方法,结合反推技术,设计了输出反馈控制器,保证了闭环系统几乎处处有唯一解且闭环系统是几乎处处渐近稳定的.数值仿真验证了输出反馈控制器的有效性.     

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考察一类Markov切换时变时滞随机系统的均方指数稳定性. 利用基于Liapunov函数和线性矩阵不等式的方法, 给出了使状态反馈控制系统能克服不确定性和随机干扰, 在均方意义下达到指数稳定的充分条件. 当Markov链遍历所有模态时, 给出了一个独立于Markov链模态集的增益矩阵, 使得状态反馈控制系统均方指数稳定     

Stability for multi-linked stochastic delayed complex networks with stochastic hybrid impulses by Dupire Itô’s formula

In this paper, the mean-square exponential stability is investigated for multi-linked stochastic delayed complex networks with stochastic hybrid impulses. Distinct from the existing literature, we study the MSDCNs on the basis of the multi-linked stochastic functional differential equations that consider the impact of a certain past interval on the present. Moreover, the stochastic hybrid impulses we discuss possess stochastic impulsive moments and impulsive gain, which make the impulses fit better to the real-world demands for control. Also, a novel concept of average stochastic impulsive gain is proposed to measure the intensity of the stochastic hybrid impulses. By the use of Dupire Itô’s formula, based on Lyapunov method, graph theory and stochastic analysis techniques, two sufficient criteria for the mean-square exponential stability are derived, which are closely related to average stochastic impulsive gain, stochastic disturbance strength as well as the topological structure of the network itself. Finally, an application about neural networks is discussed and corresponding numerical example is presented to demonstrate the feasibility and effectiveness of the theoretical results.     

On exponential stability of second order delay differential equations

We propose a new method for studying stability of second order delay differential equations. Results we obtained are of the form: the exponential stability of ordinary differential equation implies the exponential stability of the corresponding delay differential equation if the delays are small enough. We estimate this smallness through the coefficients of this delay equation. Examples demonstrate that our tests of the exponential stability are essentially better than the known ones. This method works not only for autonomous equations but also for equations with variable coefficients and delays.     

Adaptive stabilization for a Kirchhoff-type nonlinear beam under boundary output feedback control

In this paper, the boundary stabilization for a Kirchhoff-type nonlinear beam with one end fixed and control at the other end is considered. A gain adaptive controller is designed in terms of measured end velocity. The existence and uniqueness of the classical solution of the closed-loop system are justified. The exponential stability of the system is obtained.     

Periodic oscillatory solution in delayed competitive–cooperative neural networks: A decomposition approach

In this paper, the problems of exponential convergence and the exponential stability of the periodic solution for a general class of non-autonomous competitive–cooperative neural networks are analyzed via the decomposition approach. The idea is to divide the connection weights into inhibitory or excitatory types and thereby to embed a competitive–cooperative delayed neural network into an augmented cooperative delay system through a symmetric transformation. Some simple necessary and sufficient conditions are derived to ensure the componentwise exponential convergence and the exponential stability of the periodic solution of the considered neural networks. These results generalize and improve the previous works, and they are easy to check and apply in practice.     

LMI based design of constrained fuzzy predictive control

Predictive control of nonlinear systems subject to output and input constraints is considered. A fuzzy model is used to predict the future behavior. Two new ideas are proposed here. First, an added constraint on the applied control action is used to ensure the decrease of a quadratic Lyapunov function, and so guarantee Lyapunov exponential stability of the closed-loop system. Second, the feasibility of the finite-horizon optimization problem with the added constraints is ensured based on an off-line solution of a set of LMIs. The novel stability method is compared to the existing methods, such as the techniques based on the end-point constraints (terminal constraint set), and the robust stability techniques based on the small gain theory. The proposed method ensures Lyapunov exponential stability, does not need an auxiliary controller and can be used with any feasible controller parameters. Illustrative examples including the predictive control of a highly nonlinear chemical reactor (CSTR) are discussed.     

参数不确定非自治混沌系统的自适应指数同步

针对参数不确定非自治混沌系统,研究了指数同步问题。给出了自适应控制器的构造方法,并运用Lyapunov稳定性定理证明了在该控制器下的误差系统是指数稳定的,且可以通过调整控制参数控制同步时间。最后,利用MATLAB软件对两个含有不确定参数的非自治混沌系统进行了数值仿真,验证了所提出方法的有效性和正确性.     

Razumikhin-type theorems on exponential stability of impulsive delay systems

^** Corresponding author. Email: xzliu{at}math.uwaterloo.ca This paper studies the exponential stability of impulsive delaysystems. By employing the Razumikhin technique and Lyapunovfunctions, several exponential stability criteria are establishedfor both linear and non-linear impulsive delay systems. Someexamples are also worked through to illustrate our results.     

Existence,uniqueness and stability results of random impulsive semilinear differential systems

In this paper, we consider semilinear differential systems with random impulses. We study the existence and uniqueness of the solutions by relaxing the linear growth conditions, sufficient conditions for stability through continuous dependence on initial conditions and the exponential stability of this system have been established.     

带跳随机微分方程的Euler-Maruyama方法的几乎处处指数稳定性和矩稳定性

本文首先研究了一维带跳随机微分方程的指数稳定性,并证明Euler-Maruyama(EM)方法保持了解析解的稳定性.其次,研究了多维带跳随机微分方程的稳定性,证明若系数满足全局Lipchitz条件,则EM方法能够很好地保持解析解的几乎处处指数稳定性、均方指数稳定性.最后,给出算例来支持所得结论的正确性.