An adaptive strategy for controlling chaotic system

This paper presents an adaptive strategy for controlling chaotic systems. By employing the phase space reconstruction technique in nonlinear dynamical systems theory, the proposed strategy transforms the nonlinear system into canonical form, and employs a nonlinear observer to estimate the uncertainties and disturbances of the nonlinear system, and then establishes a state-error-like feedback law. The developed control scheme allows chaos control in spite of modeling errors and parametric variations. The effectiveness of the proposed approach has been demonstrated through its applications to two well-known chaotic systems : Duffing oscillator and Rǒssler chaos.     

Hybrid internal model control and proportional control of chaotic dynamical systems

A new chaos control method is proposed to take advantage of chaos or avoid it. The hybrid Internal Model Control and Proportional Control learning scheme are introduced. In order to gain the desired robust performance and ensure the system‘s stability, Adaptive Momentum Algorithms are also developed. Through properly designing the neural network plant model and neural network controller, the chaotic dynamical systems are controlled while the parameters of the BP neural network are modified. Taking the Lorenz chaotic system as example, the results show that chaotic dynamical systems can be stabilized at the desired orbits by this control strategy.     

Using chaos to improve measurement precision

If the measuring signals wore input to the chaotic dynamic system as initial parameters, the system outputs might be in steady state, periodic state or chaos state. If the chaotic dynamic system outputs controlled in the periodic states, the periodic numbers would be changed most with the signals. Our novel method is to add chaotic dynamic vibration to the measurement or sensor system. The sensor sensitivity and precision of a measurement system would be improved with this method. Chaotic dynamics measurement algorithms are given and their sensitivity to parameters are analyzed in this paper. The effects of noises on the system are discussed,     

Adaptive Anti-Synchronization Between Different Chaotic/Hyperchaotic Systems with Fully Unknown Parameters

The anti-synchronization between different chaotic/hyperchaotic systems with fully unknown parameters is considered in detail. Based on Lyapunov stability theory, the adaptive control schemes and parameter update rules are designed in this paper. Two numerical examples show the effectiveness and feasibility of the proposed method.     

Modified Projective Synchronization of a New Hyperchaotic System with Known or Unknown Parameters

This work presents two different methods-- nonlinear control method and adaptive control approach to achieve the modified projective synchronization of a new hyperchaotic system with known or unknown parameters. Based on Lyapunov stability theory, nonlinear control method is adopted when the parameters of driving and response systems are known beforehand; when the parameters are fully unknown, adaptive controllers and parameters update laws are proposed to synchronize two different hyperchaotic system and identify the unknown parameters. Moreover, the rate of synchronization can be regulated by adjusting the control gains designed in the controllers. The corresponding simulations are exploited to demonstrate the effectiveness of the proposed two methods.     

Impulsive Control and Synchronization of a Critical Chaotic System

This paper investigates the impulsive control and synchronization of a chaotic system, which is a particular case of the so-called generalized Lorenz canonical form （GLCF） with r τ -1 Based on the impulsive control method, some new criteria are obtained to guarantee the impulsively controlled chaotic system and error system to be globally asymptotically stable at origin. Moreover, to be some simulation results are included to visualize the effectiveness and feasibility of the proposed method.     

Application of chaotic theory to parameter estimation

High precision parameter estimation is very important for control system design and compensation. This paper utilizes the properties of chaotic system for parameter estimation. Theoretical analysis and experimental results indicated that this method has extremely high sensitivity and resolving power. The most important contribution of this paper is apart from the traditional engineering viewpoint and actualizing parameter estimation just based on unstable chaotic systems.     

Realization of finite precision chaotic systems via internal perturbation

A method of controllable internal perturbation inside the chaotic map is proposed to solve the problem in chaotic systems caused by finite precision.A chaotic system can produce large amounts of initial-sensitive,non-cyclical pseudo-random sequences.However,the finite precision brings short period and odd points which obstruct application of chaos theory seriously in digital communication systems.Perturbation in chaotic systems is a possible efficient method for solving finite precision problems,but former researches are limited in uniform distribution maps.The proposed internal perturbation can work on both uniform and non-uniform distribution chaotic maps like Chebyshev map and Logistic map.By simulations,results show that the proposed internal perturbation extends sequence periods and eliminates the odd points,so as to improve chaotic performances of perturbed chaotic sequences.     

Parameter self-adaptive synchronization control for a kind of financial chaotic systems

A parameter adaptive control approach was applied to a kind of financial chaotic systems. According to Lyapunov stability theorem, synchronization of two financial chaotic systems with different certain parameters or the same uncertain parameters were implemented through designing proper control functions and using parameters selfadaptive control principle. The sufficient synchronization conditions of the two financial systems were obtained. Under the situation of the same uncertain parameters, the synchronization system has simpler controller and better performance. Numerical simulations show the effectiveness of the method.     

Adaptive Excitation Control with L2 Disturbance Attenuation for Multi-Machine Power Systems

Generator excitation control plays an important role in improving the dynamic performance and stability of power systems. This paper is concerned with nonlinear decentralized adaptive excitation control for multi-machine power systems. Based on a recursive design method, an adaptive excitation control law with L2 disturbance attenuation is constructed. Furthermore, it is verified that the proposed control scheme possesses the property of decentralization and the robustness in the sense of L2-gain. As a consequence, transient stability of a multi-machine power system is guaranteed, regardless of system parameters variation and faults.     

四阶混沌电力系统的全局快速滑模控制器设计

为四阶混沌电力系统设计具有全局快速收敛特性的储能型滑模控制器。首先,构建了具有储能装置的受控电力系统,利用混沌理论的基本分析方法对原有四阶电力系统的混沌振荡现象进行分析。然后,将受控电力系统的混沌控制问题转化为二阶非线性系统的控制,为二阶非线性系统定义新型滑模面并与已有滑模面进行比较,从而论证其在克服抖振及奇异问题时具有优越性,并为该非线性系统提出具有全局快速性能的滑模控制方法。最后,将该滑模控制方法用于设计电力系统混沌控制器并通过数值仿真证实控制器的有效性。本文方法的重要特点在于能够凸显电力系统混沌控制的基本规律。     

一类Mathieu方程的混沌分析及控制

利用数值仿真的方法,对一类Mathieu方程的混沌运动及其控制进行了研究.利用分岔图、Lyapunov指数谱和相图等揭示了该系统经由倍周期分岔通向混沌的路径.采用二次分段函数作为非线性反馈控制器,通过控制后方程的分岔图选择适当的控制参数,对这一类Mathieu方程中的混沌行为进行有效的控制.     

一个混沌复系统的同步与混沌控制

本文对一个三维的混沌复系统的同步和混沌控制问题进行了研究.首先分析该复系统的基本性质,然后在系统参数未知的情况下,实现了系统的自适应混沌同步和参数识别.数值仿真验证了所设计的控制器和未知参数辨识规则的有效性.最后利用线性反馈控制法实现了系统的混沌控制.     

混沌系统的最优反同步

近年来,混沌同步问题是混沌控制中的一个热点问题,本文在参数未知的情况下,通过设计最优控制器和参数自适应律实现了新的四维混沌系统与超混沌吕系统的反同步,接着根据Lyapunov稳定性原理和Hamilton-Jacobi-Bellman方程,选取Lyapunov函数和合适的性能指标函数从理论上证明这种方法的有效性.理论证明结果表明本文所设计的控制器能使性能指标函数取得最小值,是最优的.最后又通过matlab软件对反同步系统进行数值仿真,仿真结果表明驱动系统与响应系统能够很好地达到了同步,说明这种方法是可行有效的.     

Chen系统的混沌控制研究

研究Chen系统的混沌运动,并对Chen’s混沌系统进行控制.运用比例微分控制器控制方法将其混沌系统控制到稳定的周期轨道,同时设计了一种含参控制器,使受控系统追踪控制到一维参考信号和任意目标点,运用Matlab进行数值仿真,经验证Chen’s混沌系统可以得到快速有效的控制.     

一种控制混沌吸引子不稳定周期轨道的新方法

提出一种控制混沌吸引子不稳定周期轨道的新方法。该方法先从系统映图中找出混沌吸引子不稳定不动点的近似值,然后利用非线性反馈达到控制混沌的目的。这种方法的主要特点是不需要知道混沌系统的具体模型,且可以在混沌态的任意时刻施加控制作用,另外,该方法还具有很强的抗干扰能力和非常快的快速速度,控制结构简单,易于实现。仿真结果表明了该方法的有效性。     

一个新分数阶混沌系统的同步和控制

构造了一个具有三个非线性二次项的新分数阶混沌系统,分析了其基本的混沌动力学特性,并应用Laplace变换实现了新系统的混沌控制。基于Lyapunov理论和分数阶混沌系统稳定性理论,得到同时实现新分数阶混沌系统自适应同步和参数辨识的充分条件,并通过数值仿真,验证了结论的正确性。     

特殊系统的混沌轨道引导控制

混沌控制的研究和发展 ,使非线性科学理论在实际应用中出现了巨大的突破 无论是根据实际问题的需要抑制混沌 ,还是利用混沌的特性获得新的动力学途径 ,混沌使动力学的应用呈现出多样性 由于混沌轨道的遍历性 ,使人们能够利用这种遍历性对动力系统进行有选择的利用 利用混沌控制的思想 ,笔者提出了混沌轨道之间引导控制的概念 ,通过Melnikov函数讨论了平面Hamilton系统的轨道控制项满足的条件 文中就一类特殊动力系统具体讨论了轨道引导控制实现及数值模拟