基于观测器的不确定混沌系统同步

提出了一类混沌系统的观测器同步方法。利用混沌系统的不确定项观测器,给出了一类混沌系统基于观测器同步的简单有效方法,该方法不需知道外部扰动的任何信息,且观测器的设计方法简单,利于工程应用。通过对Lorenz混沌系统的分析和数值模拟研究,验证了该方法在混沌同步中的优良性能。     

基于状态观测器的混沌动态系统跟踪控制

针对一类连续混沌动态系统,提出一种基于状态观测器的跟踪控制方法来进行混沌控制.在引入状态观测器观测混沌动力学系统状态变量的基础上,采用反馈线性化方法将非线性混沌系统转换为线性系统,再针对反馈线性化后的线性系统设计轨迹跟踪控制器,实现被控混沌系统的跟踪控制.仿真结果进一步验证了该方法的有效性.     

混沌系统的混合同步及其在安全通信中的应用

提出了一类混沌系统的混合同步方法。利用非线性系统的状态观测器，给出了一类混沌系统的同步和安全通信的简单有效的方法，并分析了系统的稳定性，对Rossler混沌系统的分析和仿真研究表明，该方法在混沌同步及安全通信中具有同步速度快、系统精度高等优良性能。     

基于精确线性化的Nadolschi混沌系统T—S模糊控制

针对一类新的混沌系统--Nadolschi混沌系统,提出一种新的模糊镇定控制方法.该方法首先利用T-S模糊模型对Nadolschi混沌系统进行精确描述,在此T-S模糊模型的基础上,基于并行分布补偿(PDC)技术和精确线性化(EL)理论设计模糊状态反馈控制器来镇定Nadolschi混沌系统,并且利用线性系统理论证明了闭环系统的渐近稳定性.仿真结果表明,设计的控制器能够快速有效地将Nadolschi混沌系统的混沌时间轨迹渐近镇定到其零平衡点,且控制简单可靠.该方法可以进一步推广到其他混沌(超混沌)系统的控制问题中.     

一类混沌系统耦合同步的充分条件及其应用

针对一类非线性项满足Lipschitz条件的混沌系统，利用Lyapunov定理研究了耦合混沌系统的同步问题，提出了耦合混沌系统同步的一个充分条件。利用经性矩阵不等式（LMI）方法和Gerschgorin定理，给出了该混沌同步条件的LMI形式和代数不等式形式。将结果应用于蔡氏电路，证明了其正确性。     

具有噪声扰动的统一混沌系统的同步控制

研究了一类具有噪声扰动的统一混沌系统的同步控制问题。基于滑模变结构控制理论,提出了利用不确定性观测器估计扰动噪声,用噪声的观测值来设计控制器的新方法,而且适当选取观测器反馈增益可以使观测误差充分的小,从而可得到几乎没有受到扰动时的控制效果。和常规滑模变结构控制方法相比,所设计的控制器既能有效地抑制抖振,又能降低控制器参数设计的保守性。最后,基于Matlab 6.5软件对Lorenz混沌系统进行分析和数值模拟,验证了该滑模控制方法在混沌同步中的优良性能。     

混沌非线性反馈密码序列的理论设计和有限精度实现

本文利用一类特殊的一维分段线性混沌系统，来产生具有均匀不变分布函数和δ自相关函数特性的连续混沌信号，这类连续混信号经过不可逆变换可生成具有理想保密性的二进制混 列。本文分析了该混沌系统的有限精度效应并提出一类ｍ序列扰动实现方法，，与传统密码序列相比，混沌非线性反馈密码序列不仅具有丰富的源泉，而且设计异常方便，性能易于控制。     

基于联合混沌系统的保密通信方法研究

提出了利用离散混沌系统联合加密来实现保密通信的方法。引用著名的Henon和Lorenz混沌系统作为仿真实验证明了其可行性，混沌系统均采用backstepping和dead-beat同步设计方案，以快速达到同步，理论分析证明，此种方法不仅是可行的，且与非联合混沌系数相比，加强了保密性。混沌屏蔽技术仿真结果也证明，该系统不仅实现简单，容易控制，而且增强了整个系统的保密性能。     

自动化技术、计算机技术

TP132008012043具有非线性输入的一类不确定混沌系统的控制/陈晶,张天平,钱厚斌(扬州大学信息工程学院计算机系)//系统工程与电子技术.―2007,29(2).―269～272.研究了一类具有非线性输入的不确定混沌系统的跟踪控制问题。首先在系统状态已知,系统的非线性项及干扰项的界已知的情况下设计了理想滑模控制器,然后在系统只有一个状态可测,非线性项及干扰项的界未知的情况下,利用扩张观测器观测出系统的未知信息再设计控制器,从而实现了混沌系统的跟踪控制。最后对Duffing系统进行数值仿真,结果表明该控制方案是有效的。图2表0参12TP132008012…     

基于Lorenz系统切换混沌同步的保密通讯

该文提出利用Lorenz系统切换混沌同步实施保密通讯的方法。构建了有一定关联的两个Lorenz混沌系统,并通过选择器在系统间随机切换;用同一种控制方法既能实现不同Lorenz系统的混沌同步,又能实现相同Lorenz系统的混沌同步;发送系统可以在Lorenz混沌系统间随机转换,传输信道中混沌调制信号也随之不断变化;接收系统将混沌调制信号解调后,即可获取有用信号。由于发送系统的可选择性,导致保密信号的多样性和随机性,因此该保密通讯方法具有更好的保密性能。     

基于线性状态反馈方法的Nadolschi混沌系统同步

研究了一类新型混沌系统——Nadolschi系统的同步控制问题。首先为响应系统设计一个多变量线性状态反馈控制器,进而将Nadolschi系统的同步控制问题转化为误差系统零平衡点的镇定问题。然后,根据Lyapunov稳定性理论,得出使Nadolschi混沌系统达到渐近同步的充分条件。仿真结果验证了所提方法的有效性,所设计的控制器具用结构简单,易于实现等优点。     

Globally Exponential Synchronization and Parameter Regulation for Coupled Chaotic System via Adaptive Control

Based on Lyapunov stability theory,an adaptive controller is designed for a class of chaotic systems. Globally exponential synchronization and parameter regulation for couple chaotic systems can be carried out simultaneously. The controller and the regulating law of parameters are directly constructed by analytic formula. Simulation results with some chaotic systems show the effectiveness of the proposed controller.     

Synchronization and Parameters Identification of Chaotic Systems via Adaptive Control

Based on Lyapunov stability theory, a novel adaptive controller is designed for a class of chaotic systems. The parameters identification and synchronization of chaotic systems can be carried out simultaneously. The controller and the updating law of parameters identification are directly constructed by analytic formula. Simulation results with Chen‘s system and Roessler system show the effectiveness of the proposed controller.     

Taming Single Input Chaotic Systems by Fractional Differentiator-Based Controller: Theoretical and Experimental Study

A simple fractional differentiator-based controller is proposed to suppress chaos in a 3D single input chaotic system by stabilizing some of the fixed points. The tuning procedure for the proposed controller is based on the stability concepts in the incommensurate fractional order systems. To show the efficiency of the controller, some numerical simulations are given. Also, to evaluate the practical capability of the proposed controller, we experimentally apply it to control chaos in a chaotic circuit. Moreover, some mathematical analyses are presented to show the applicability of the proposed controller, when its structure is not exactly implementable.     

Synchronization of Chaotic Systems Using Time-Delayed Fuzzy State-Feedback Controller

This paper presents the fuzzy-model-based control approach to synchronize two chaotic systems subject to parameter uncertainties. A fuzzy state-feedback controller using the system state of response chaotic system and the time-delayed system state of drive chaotic system is employed to realize the synchronization. The time delay which complicates the system dynamics makes the analysis difficult. To investigate the system stability and facilitate the design of fuzzy controller, Takagi-Sugeno (T-S) fuzzy models are employed to represent the system dynamics of the chaotic systems. Furthermore, the membership grades of the T-S fuzzy models become uncertain due to the existence of parameter uncertainties which further complicates the system analysis. To ease the stability analysis and produce less conservative analysis result, the membership functions of both T-S fuzzy models and fuzzy controller are considered. Stability conditions are derived using Lyapunov-based approach to aid the design of fuzzy state-feedback controller to synchronize the chaotic systems. Simulation examples are presented to illustrate the merits of the proposed approach.     

基于投影法的不确定分数阶混沌系统自适应同步

针对一类具有未知参数、未知非线性函数及外部扰动的分数阶混沌系统,基于分数阶系统稳定性理论和Lyapunov稳定性理论,该文提出一种基于滑模自适应和投影法的同步控制策略。首先选取一类稳定的分数阶积分滑模面,运用自适应技术对不确定项进行估计,设计了同步控制器。然后对自适应设计中容易出现的增长型自适应律运用投影法进行修正,以保证参数有界,从而也保证控制输入有界。最后数值仿真证明了所设计控制器的正确性和有效性。     

混沌动力学系统的神经网络学习控制研究

针对混沌动力学系统建模困难，控制不易实现，存在干扰等特点，在附加动量法的自适应BP网络的基础上，研究了混沌动力学系统的学习控制策略。构建了混沌动力学系统的NN模型和NN控制器，对混沌系统在学习的同时施加控制，仿真实验结果表明，该控制策略具有鲁棒性强，有良好的适应性，网络参数训练时间短等优点。     

A Control Lyapunov Function Approach to Stabilization of Affine Nonlinear Systems with Bounded Uncertain Parameters

This paper considers the robust stabilization problem of a class of affine nonlinear systems with bounded uncertain time-invariant parameters. A robust control Lyapunov function (RCLF) is introduced for the considered system. Based on the RCLF, a globally asymptotically stabilizing controller is then designed. The proposed controller is robust under the variant of system parameters. As the applications of the proposed scheme, the stabilization of uncertain feedback linearizable systems and the unified chaotic system are investigated, respectively. A numerical example on the unified chaotic system is also provided to illustrate the effectiveness of the presented method.     

Stabilizing periodic solutions of nonlinear systems and applications in chaos control

In this paper, a simple nonlinear recursive delayed feedback controller is designed for stabilizing periodic solutions of a nonlinear system. The proposed controller is constructively designed and does not inherit the odd number limitation. The stability of the periodic solution of the closed-loop system is proved rigorously. Applying the control method to chaotic systems, one can effectively control chaos.     

Adaptive Fuzzy Control of Nonlinear in Parameters Uncertain Chaotic Systems Using Improved Speed Gradient Method

This paper presents an adaptive fuzzy controller for Nonlinear in Parameters (NLP) chaotic systems with parametric uncertainties. In the proposed controller, the unknown parameters are estimated by the novel Improved Speed Gradient (ISG) method, which is a modification of Speed Gradient (SG) algorithm. ISG employs the Lagrangian of two suitable objective functionals for on-line estimation of system parameters. The most significant advantage of ISG is that it is applicable to NLP systems and it results in a faster rate of convergence for the estimated parameters than the SG method. Estimated parameters are used to design the fuzzy controller and to calculate the Lyapunov exponents of the chaotic system adaptively. Furthermore, established on the well-known Takagi–Sugeno (T-S) fuzzy model, a LMI (Linear Matrix Inequality)-based fuzzy controller is designed and is tuned using estimated parameters and Lyapunov exponents. Throughout the controller design procedure, several important issues in fuzzy control theory including relaxed stability analysis, control input performance specifications, and optimality are taken into account. Combination of ISG parameter estimation method and T-S-based fuzzy controller yields an adaptive fuzzy controller capable to suppress uncertainties in parameters and initial states of NLP chaotic systems. Finally, simulation results are provided to show the effectiveness of the ISG and adaptive fuzzy controller on chaotic Lorenz system and Duffing oscillator.