统一混沌系统的全局指数吸引集的新结果

研究了参数α∈[1/29,14/173)时,统一混沌系统的全局指数吸引集问题.通过线性变换和广义Lyapunov函数方法,给出了系统最终上界的精确估计.所得结果发展和丰富了现有混沌系统吸引集的结果,并将在混沌控制和同步中得到广泛应用.     

Chen混沌系统的非线性全局同步控制

研究了Chen提出的一个新的混沌系统的混沌同步问题,利用非线性控制方法设计了三种混沌同步控制器,并用李雅普诺夫方法证明了在混沌控制器作用下,驱动、响应混沌系统可以实现全局同步.数值仿真结果表明,所设计的三种混沌控制器都能有效的实现混沌同步,并且具有很强的鲁棒性.     

多涡旋混沌同步和分数阶混沌同步

为探讨混沌同步现象和相应的动力学特性,研究了两类特殊的混沌系统即多涡旋混沌系统和分数阶混沌系统的同步.为此,设计了一种非线性反馈控制器,实现了多涡旋类Lorenz的混沌吸引子的投影同步;通过改变投影同步的比例系数,获得了与激励系统相对应的状态变量的任意比例输出.此设计还实现了分数阶超混沌系统的状态向量与任意信号的追踪同步,从而控制分数阶混沌信号趋于期望的周期轨道或平衡点,并实现分数阶混沌系统与整数阶混沌系统的异构追踪同步.最后设计了具有分数阶混沌特性的电路,借助仿真实验证实了分数阶超混沌系统的动力学行为.这些研究结果可以应用于许多领域,例如宏观经济系统的数据分析、保密通讯系统分析与设计等.     

一类不确定混沌系统的自适应同步

讨论了混沌系统的同步问题 .对一类不确定混沌系统 ,提出了一个新的自适应同步方法 ,可使响应系统在自适应控制器的控制下 ,实现与不确定混沌系统的同步 .最后给出了一个设计实例 .     

带有不确定参数的一类混沌金融系统的广义投影同步

针对带有不确定参数的一类混沌金融系统,提出了实现驱动系统和响应系统广义投影同步的自适应控制策略,并基于Lyapunov稳定性理论给出和验证了广义投影同步稳定性判据.数值仿真验证了控制策略和理论分析的有效性.     

基于主动滑模控制的混沌系统函数投影同步

研究了一类混沌系统的函数投影同步问题.基于Lyapunov稳定性理论和主动滑模控制方法,设计了主动滑模控制器,实现混沌系统的函数投影同步.数值仿真验证了该控制器的有效性和正确性.     

含有不确定项的混沌系统自适应广义同步

针对一类含有不确定项的混沌系统,设计了广义同步响应系统,利用系统稳定性理论设计了自适应广义同步控制器及自适应率,实现了驱动系统和所设计的响应系统广义同步,所设计的控制策略对外界干扰有较强的鲁棒性,而且通过引入加速因子,可任意配置同步响应速度,具有较高的应用价值,理论分析及仿真结果验证了该方法的有效性。     

广义符号动力系统的混沌性

本文给出了符号动力系统的一般数学模型,它是离散时空系统的一种特殊情形.在现有离散时空系统的混沌概念和研究方法的基础上.研究了这类广义符号动力系统的混沌性,得到了一类在Devaney意义下新的广义符号混沌动力系统,从而推广了现有符号动力系统混沌性的研究范围.     

受扰不确定混沌系统的降阶修正函数投影同步

研究了具有不同阶数的受扰不确定混沌系统的降阶修正函数投影同步问题.基于Lyapunov稳定性理论和自适应控制方法,设计了统一的非线性状态反馈控制器和参数更新规则,使得混沌响应系统按照相应的函数尺度因子矩阵和混沌驱动系统的部分状态变量实现同步.方法考虑了实际系统中的模型不确定性和外界扰动,具有较强的实用性和鲁棒性.数值仿真证明了控制方法的有效性.     

异维混沌动力系统的有限时间广义同步

本文研究了异维混沌动力系统的有限时间广义同步的问题.利用有限时间Lyapunov稳定性定理、Jensen不等式等理论方法,通过设置不同的控制器,从理论上提出了一般的异维驱动系统和响应系统的有限时间广义同步的两种方案,并且对方案二中的影响同步时间因素做了理论分析和证明.最后,数值模拟验证了提出理论的正确性和可行性.     

Existence of an optimal control for a coupled FBSDE with a non degenerate diffusion coefficient

We consider a controlled system driven by a coupled forward–backward stochastic differential equation with a non degenerate diffusion matrix. The cost functional is defined by the solution of the controlled backward stochastic differential equation, at the initial time. Our goal is to find an optimal control which minimizes the cost functional. The method consists to construct a sequence of approximating controlled systems for which we show the existence of a sequence of feedback optimal controls. By passing to the limit, we establish the existence of a relaxed optimal control to the initial problem. The existence of a strict control follows from the Filippov convexity condition.     

随机非线性物价模型的最优控制

将政府对价格系统的宏观调控作为外部控制力,建立受控的随机非线性物价模型;利用拟Hamilton系统随机平均法和随机动态规划原理的非线性随机控制策略对系统实施最优控制,控制目标是实现系统的稳定性变大;并通过对比控制前后的Lyapunov指教值说明了控制的有效性.     

Adaptive robust control of artificial swarm systems

We consider an artificial swarm system consisting of multi-agents. The agents may interact with each other based on their relative positions. Each agent exhibits a repulsion/attraction behavior toward another agent, which mimics some biological swarm systems. The performance of each individual agent is the accumulation of these respective considerations toward other agents. The overall performance of the artificial swarm system mimics the aggregation and formation in biological systems. We propose an adaptive robust control for each agent toward achieving the performance. The control can withstand uncertainty, which is time-varying, nonlinear, and without known bound. The controlled system converges to the desirable swarm system performance regardless of the uncertainty.     

Ergodic and adaptive control of hidden Markov models

A partially observed stochastic system is described by a discrete time pair of Markov processes. The observed state process has a transition probability that is controlled and depends on a hidden Markov process that also can be controlled. The hidden Markov process is completely observed in a closed set, which in particular can be the empty set and only observed through the other process in the complement of this closed set. An ergodic control problem is solved by a vanishing discount approach. In the case when the transition operators for the observed state process and the hidden Markov process depend on a parameter and the closed set, where the hidden Markov process is completely observed, is nonempty and recurrent an adaptive control is constructed based on this family of estimates that is almost optimal.     

Parametric control of solutions to an evolution problem in a neighborhood of an unstable stationary regime

We study a controlled system of ordinary differential equations in a neighborhood of an unstable stationary regime. We seek for a control under which the solution remains in the neighborhood however long. We find conditions under which such control is possible and prove an existence theorem. The results are of a constructive character and can be applied to controlling actual processes.     

Multitime Controllability,Observability and Bang-Bang Principle

Control problems for multitime first-order PDE arise in many different contexts and ways. The obstruction of complete integrability conditions (path independent curvilinear integrals) has determined the mathematicians to study such problems only in the discrete context, though thus they loose the geometrical character which is proper to the continuous approach. In this paper, we study controllability, observability and bang-bang properties of multitime completely integrable autonomous linear PDE systems, overcoming the existent mathematical prejudices regarding the importance of a multitime evolution of m-flow type. Our geometrical arguments show that each basic theorem has a correspondent in the case of a single-time linear controlled ODE system. The main results include controllability criteria, equivalence between controllability of a PDE system and observability of the dual PDE system, geometry of the control set, extremality and multitime bang-bang principle. All of these show that the passing from controlled single-time evolution (1-flow) to the controlled multitime evolution (m-flow) is not trivial. Changing the geometrical language, the case of nonholonomic evolution can be recovered easily from our theory.     

Avoiding extremes using partial control

Dynamical systems can be prone to severe fluctuations due to the presence of chaotic dynamics. This paper explains for a toy chaotic economic model how such a system can be regulated by the application of relatively weak control to keep the system confined to a bounded region of the phase space, even in the presence of strong external disturbances. Since the control here is weaker than the disturbance, the system cannot be controlled to a particular trajectory, but under certain circumstances it can be partially controlled to avoid extreme values. Partial control depends on the existence of a certain set called a ‘safe sets’. We describe the safe set and how it varies with parameters, sometimes continuously and sometimes discontinuously.     

Complicated version of a robust control scheme

A new robust control design is introduced. The worst cases of controlled system performance and control magnitude are both investigated. Their comparison with early counterparts is also made.     

Controlling hyperchaos in hyperchaotic Lorenz system using feedback controllers

In this paper, the control strategies for hyperchaotic Lorenz system is investigated. The ordinary, dislocated, enhancing and speed feedback controls are used to suppress hyperchaos to unstable equilibrium. The Routh-Hurwitz criterion is used to derive the conditions of stability of the controlled hyperchaotic systems. It is found that the coefficients of enhancing feedback control and dislocated feedback control may be smaller than those of ordinary feedback control, so, the complexity and cost of the system control are reduced. Numerical simulations are given to illustrate the effectiveness of the proposed controllers.