A parameter estimator based on adaptive noise canceller

I.Introductionwith'thewendevelopmentofadaptivesignalprocessingtheoryandtheraPiddevelopmentofD.S.Pdevices,adaptivenoisecancellerl1'2]iswidelyusedininformationprocessingfieldssuchasradar,sonartspeechsignalprocessingandcommunication.Butadaptivecancellerisseldomusedasaparameterestimatortoestimateaprocessorparameterssuchasbearing,rangetvelocityandpositionofamaneuveringtarget,becausetheparameters(i.e.thesrycalledsignaltobeestimatied)tobeestimatedareusuallynonstationaryandhavethenonzeromean,thatwill…     

一种采用脉冲串的自适应有源干扰抵消器

在许多应用中，周期性干扰是由旋转的机械设备所产生的。一个周期性信号可以与一个特殊形式的周期性的脉冲串完全相干。本文提出了一种采用脉冲串的自适应有源噪声抵消器(AANC)来抵消周期性干扰，这种抵消器产生一个与干扰信号相同步的周期性的单位脉冲串作为参考输入。将这种有源噪声抵消器和Delayed-X LMS算法相结合，可以大大地减小运算量，并且也可以保证良好的收敛特性。理论分析和计算机仿真验证了本文的结果。     

Synchronization between two different chaotic systems with noise perturbation

This paper investigates the chaotic synchronization between the noise-perturbed Lorenz system and one of the noise-perturbed Chen and Lu¨ systems.Based on the active control method and the Lyapunov theory in stochastic differential equations,sufficient conditions for the stability of the error dynamics are derived.Numerical simulations are also shown to demonstrate the effectiveness of these theoretic results.     

混沌时间序列多步自适应预测方法

针对混沌时间序列局域自适应预测方法在多步预测中预测器系数无法调节的问题，根据混沌时间序列的短期可预测性及自适应算法的自适应跟踪混沌运动轨迹的特点，提出了混沌时间序列多步自适应预测方法.仿真结果表明，此方法的多步预测性能明显好于局域自适应预测方法的多步预测性能. 关键词： 多步自适应预测方法 局域自适应预测方法 混沌时间序列     

基于在线误差修正自适应SVR的非线性不确定分数阶混沌系统滑模控制

提出了一种基于在线误差修正自适应SVR的滑模控制方法, 用于解决一类非线性不确定分数阶混沌系统的控制问题. 分别通过对混沌系统非线性函数的离线SVR估计和基于增量学习的状态跟踪误差在线SVR预测, 解决了不确定分数阶混沌系统模型难以预测的问题. 同时根据Lyapunov稳定性理论设计出SVR权值自适应调整律. 本文以分数阶Arneodo 系统为例进行仿真, 仿真结果表明了, 对于带有外界噪声扰动的非线性不确定分数阶混沌系统, 该方法可以在有限时间内将系统稳定至期望状态, 提高对非线性函数的预测精度, 改善控制性能.     

Modified adaptive controller for synchronization of incommensurate fractional-order chaotic systems

We investigate the synchronization of a class of incommensurate fractional-order chaotic systems,and propose a modified adaptive controller for fractional-order chaos synchronization based on the Lyapunov stability theory,the fractional order differential inequality,and the adaptive strategy.This synchronization approach is simple,universal,and theoretically rigorous.It enables the synchronization of0 fractional-order chaotic systems to be achieved in a systematic way.The simulation results for the fractional-order Qi chaotic system and the four-wing hyperchaotic system are provided to illustrate the effectiveness of the proposed scheme.     

利用白噪声实现混沌系统线性广义同步的研究

给定一个混沌驱动系统和同步函数，通过服从白噪声分布的单向耦合，构造出混沌响应系统，使之与驱动系统达到线性广义同步化.研究发现，利用满足一定条件的白噪声可以实现驱动-响应系统的线性广义同步.以Chua电路为例进行了数值仿真，其结果与理论计算相一致. 关键词： 混沌系统 广义同步 白噪声     

最小均方误差解调算法在彩色超声血流成像中的研究

研究了最小均方误差正交解调算法在超声血流成像中的应用。首先由设计的期望信号与接收信号在最小均方误差原则下得到其迭代解调形式,获得回波信号同相分量和正交分量,然后由得到的正交解调信号通过自相关的方法对血流流速进行估计。解调算法的仿真结果表明,对高斯噪声信噪比为0.5—10dB的正弦波调制信号,解调输出平均信噪比与Hilbert变换法和I/Q解调法相比分别提高了15dB和4dB;血流成像的仿真结果表明,在流速估计性能相当的情况下,解调的乘法运算量仅分别为上述对比方法的18%和9%。因此在超声血流成像中应用最小均方误差正交解调算法,对于提高估计性能和降低运算量都有一定意义。     

最小均方误差解调算法在彩色超声血流成像中的研究

研究了最小均方误差正交解调算法在超声血流成像中的应用。首先由设计的期望信号与接收信号在最小均方误差原则下得到其迭代解调形式,获得回波信号同相分量和正交分量,然后由得到的正交解调信号通过自相关的方法对血流流速进行估计。解调算法的仿真结果表明,对高斯噪声信噪比为0.5¹0 dB的正弦波调制信号,解调输出平均信噪比与Hilbert变换法和I/Q解调法相比分别提高了15 dB和4 dB;血流成像的仿真结果表明,在流速估计性能相当的情况下,解调的乘法运算量仅分别为上述对比方法的18%和9%。因此在超声血流成像中应用最小均方误差正交解调算法,对于提高估计性能和降低运算量都有一定意义。     

含噪混沌时间序列预测误差分析

对于含噪混沌时间序列预测问题, 传统方法存在较大的经验性, 对预测误差的构成分析不足, 因而忽略了混沌动态重建与预测模型建立之间的差异性. 本文将实际预测误差分解为预测器偏差和输入扰动误差, 并对整体最小二乘和正则化两种全局预测方法进行分析比较, 进而说明整体最小二乘适用于混沌动态的重建, 对预测器偏差影响较大, 而正则化方法能够改善预测器敏感性, 对输入扰动误差影响较大. 通过两个仿真实例, 展示了混沌动态重建与预测模型建立之间的差异, 在对比最小二乘和正则化方法的同时验证了实际预测误差受预测器偏差和输入扰动误差共同作用. 并指出, 在实际操作时应在二者间寻求平衡, 以便使模型预测精度达到最优. 关键词： 混沌时间序列预测 噪声 整体最小二乘 正则化     

Parameter estimation for chaotic systems with and without noise using differential evolution-based method

We present an approach in which the differential evolution (DE) algorithm is used to address identification problems in chaotic systems with or without delay terms. Unlike existing considerations, the scheme is able to simultaneously extract (i) the commonly considered parameters, (ii) the delay, and (iii) the initial state. The main goal is to present and verify the robustness against the common white Guassian noise of the DE-based method. Results of the time-delay logistic system, the Mackey-Glass system and the Lorenz system are also presented.     

A single adaptive controller with one variable for synchronization of fractional-order chaotic systems

In this paper we investigate the synchronization of a class of three-dimensional fractional-order chaotic systems.Based on the Lyapunov stability theory and adaptive control technique,a single adaptive-feedback controller is developed to synchronize a class of fractional-order chaotic systems.The presented controller which only contains a single driving variable is simple both in design and in implementation.Numerical simulation and circuit experimental results for fractional-order chaotic system are provided to illustrate the effectiveness of the proposed scheme.     

Fractional-order permanent magnet synchronous motor and its adaptive chaotic control

In this paper we investigate the chaotic behaviors of the fractional-order permanent magnet synchronous motor(PMSM).The necessary condition for the existence of chaos in the fractional-order PMSM is deduced.And an adaptivefeedback controller is developed based on the stability theory for fractional systems.The presented control scheme,which contains only one single state variable,is simple and flexible,and it is suitable both for design and for implementation in practice.Simulation is carried out to verify that the obtained scheme is efficient and robust against external interference for controlling the fractional-order PMSM system.     

一种分数阶混沌系统同步的自适应滑模控制器设计

针对分数阶混沌系统的同步问题, 基于滑模控制理论和自适应控制理论, 设计了一个具有较强鲁棒性的分数阶积分滑模面, 并提出了一种自适应滑模控制器在不消除非线性项的情况下实现一类三维分数阶混沌系统同步的方法. 利用所设计的自适应滑膜控制器实现了分数阶Chen系统、分数阶Liu系统以及分数阶Arneodo系统的混沌同步. 数值模拟仿真结果验证了所设计的控制器的有效性和可行性.     

Application of local polynomial estimation in suppressing strong chaotic noise

In this paper, we propose a new method that combines chaotic series phase space reconstruction and local polynomial estimation to solve the problem of suppressing strong chaotic noise. First, chaotic noise time series are reconstructed to obtain multivariate time series according to Takens delay embedding theorem. Then the chaotic noise is estimated accurately using local polynomial estimation method. After chaotic noise is separated from observation signal, we can get the estimation of the useful signal. This local polynomial estimation method can combine the advantages of local and global law. Finally, it makes the estimation more exactly and we can calculate the formula of mean square error theoretically. The simulation results show that the method is effective for the suppression of strong chaotic noise when the signal to interference ratio is low.     

Global adaptive synchronization of chaotic systems with uncertain parameters

We propose a novel adaptive synchronization method for a class of nonlinear chaotic systems with uncertain parameters.Using the chaos control method,we derive a synchronizer,which can make the states of the driven system globally track the states of the drive system asymptotically.The advantage of our method is that our problem sctting is more general than those that already exist,and the synchronizer is simply constructed by an analytic formula,without knowledge in advance of the unknown bounds of the uncertain parameters.A computer simulation example is given to validate the proposed approach.     

Persistent excitation in adaptive parameter identification of uncertain chaotic system

This paper studies the parameter identification problem of chaotic systems.Adaptive identification laws are proposed to estimate the parameters of uncertain chaotic systems.It proves that the asymptotical identification is ensured by a persistently exciting condition.Additionally,the method can be applied to identify the uncertain parameters with any number.Numerical simulations are given to validate the theoretical analysis.     

Cascade adaptive control of uncertain unified chaotic systems

The chaos control of uncertain unified chaotic systems is considered. Cascade adaptive control approach with only one control input is presented to stabilize states of the uncertain unified chaotic system at the zero equilibrium point. Since an adaptive controller based on dynamic compensation mechanism is employed,the exact model of the unified chaotic system is not necessarily required. By choosing appropriate controller parameters,chaotic phenomenon can be suppressed and the response speed is tunable. Sufficient condition for the asymptotic stability of the approach is derived. Numerical simulation results confirm that the cascade adaptive control approach with only one control signal is valid in chaos control of uncertain unified chaotic systems.     

基于自适应模糊控制的分数阶混沌系统同步

本文主要研究了带有未知外界扰动的分数阶混沌系统的同步问题.基于分数阶Lyapunov稳定性理论,构造了分数阶的参数自适应规则以及模糊自适应同步控制器.在稳定性分析中主要使用了平方Lyapunov函数.该控制方法可以实现两分数阶混沌系统的同步,使得同步误差渐近趋于0.最后,数值仿真结果验证了本文方法的有效性.