非线性ROF系统的分析和建模

在分析ROF(radio over fiber)系统组成与传输非线性的基础上,提出了用Volterra泛函级数为非线性ROF系统建立模型.研究了非线性ROF系统的Volterra级数表述、最小均方和最小二乘两种确定Volterra级数核的自适应算法在非线性ROF系统建模中的应用.通过一个用Volterra泛函级数对非线性ROF系统建模的实例,比较了Volterra LMS和Volterra RLS算法在建模中的效果,证明了用Volterra级数对非线性ROF系统建模的有效性.     

非线性Volterra系统的总体全解耦自适应滤波

研究输入、输出观测数据均受噪声干扰时的非线性Volterra系统的全解耦自适应滤波问题.基于总体最小二乘技术和Volterra滤波器的伪线性组合结构,运用约束优化问题的分析方法研究Volterra滤波过程,从而建立了一种总体全解耦自适应滤波算法.并建立了分析该算法收敛性能的参数反馈调整模型,分析表明,该算法可使各阶Volterra核稳定地收敛到真值.仿真实验的结果表明,当输入、输出观测数据均受噪声干扰时,总体全解耦自适应滤波算法的鲁棒抗噪性能和滤波精度均优于全解耦LMS自适应滤波算法.     

基于自适应Volterra滤波器的非线性系统辨识

为了识别非线性系统的参数,本文提出了一种基于自适应Volterra滤波器的非线性系统辨识方法。给出了自适应Volterra滤波器的LMS和RLS算法。数值仿真结果表明,该方法对于非线性定常和时变系统都有效。     

利用改进的BP算法实现神经网络辨识仿真

系统辨识是控制系统设计的基础。基于多层前馈神经网络结构,采用一种改进的BP算法,利用二阶梯度变尺度模型,完成了神经网络非线性系统辨识。与传统的辨识方法比较,神经网络应用于非线性系统辨识具有泛化功能和很好的容错能力,是一种不依赖模型的自适应函数估计器。采用一种改进的BP算法有效地改善了系统收敛速度慢的问题,BP模型已成为神经网络的重要模型之一,从而为控制系统正确设计奠定理论基础。     

一种基于神经网络的超稳定自适应控制算法

提出了一种用于控制复杂非线性系统的超稳定自适应控制算法。使用波波夫超稳定性原理设计控制器。用神经网络在线辨识系统的建模误差及不确定性因素，辨识结果作为补偿信号以实现系统的鲁棒控制。对一双输入双输出非线性系统的仿真结果表明，所提出的超稳定自适应控制算法具有较好的性能。     

用于在线辨识非线系统的可变正交小波网络

对于在线辨识非线性系统，传统的小波网络缺乏有效的算法。本文在正交小波网络的基础上，提出一种利于实时应用的可变正交小波网络，给出了其结构变化和参数调整的策略，并对建模误差的变化进行了分析。最后用于辨识非线性动态系统，仿真结果验证了该方法的可行性和有效性。     

基于非线性系统描述的超声马达鲁棒跟踪控制

针对行波型超声马达,在非线性系统描述的数学模型基础上,采用了一种新的鲁棒控制方案．该控制器由标称控制器和鲁棒补偿器两部分构成。首先,针对标称系统设计标称控制器得到期望的输出跟踪特性,然后加上鲁棒补偿器,实现鲁棒特性。可以证明,鲁棒稳定性、鲁棒静态特性、鲁棒瞬态特性以及鲁棒跟踪特性可同时得到．仿真和实验结果都表明了控制方案的有效性,而且该控制器结构简单、参数可在线调整.     

基于协作多点下行传输的非线性鲁棒预编码

对于协作多点系统,下行信道信息误差会大幅降低联合传输的性能。为了避免下行信道信息误差对联合传输的影响,本文利用其二阶统计特性,设计了非线性鲁棒预编码算法。由于协作多点系统的特点和非线性鲁棒预编码的结构会导致用户间的性能差异,本文通过优化非线性鲁棒预编码算法的连续干扰消除先后顺序,从而改善性能最差用户的误码率,降低非线性鲁棒预编码算法的平均误码率。仿真结果表明当下行信道信息误差存在时,本文所提出的非线性鲁棒预编码性能优于传统的线性和非线性预编码性能。仿真结果还表明优化排序能提高非线性鲁棒预编码的性能增益。     

基于神经网络的Volterra频域核辨识方法

针对目前Volterra频域核辨识方法复杂、精度不高等问题,提出一种基于神经网络的Volterra频域核辨识方法。首先选择多组频率基准确测量各阶Volterra频域核的幅值,利用BP神经网络可以任意逼近非线性函数的特点,针对不同阶Volterra频域核设计不同的神经网络模型,进行分阶辨识,最后通过一个非线性电路进行仿真验证。仿真结果表明,该方法可直接辨识频率范围内任意频率对应的Volterra频域核,过程简单、准确度高,易于工程实现。     

一种全最小二乘算法及其在非线性滤波器中的应用

针对输入输出观测数据均含有噪声的滤波问题,提出了一种稳定的总体最小二乘自适应算法。该算法以系统的增广权向量的瑞利商(RQ)与对增广权向量的最后元素的约束的和作为总损失函数,利用梯度最陡下降原理导出权向量的自适应迭代算法,并将该算法应用于非线性Volterra滤波器。研究了算法的稳定性能,提出的算法不仅有良好的收敛性能,而且在权向量的自适应迭代时不需要标准化处理,使得算法的实施更为简单。仿真实验表明,无论在线性系统或非线性系统,本文算法的收敛性能,鲁棒抗噪性能和稳态收敛精度明显高于其它同类总体最小二乘算法。     

非线性动态网络的离散算法及仿真

在非线性网络响应分析中,采用Volterra级数法可以导出与线性系统传递函数相似的非线性传递函数,能使非线性系统用线性化和系统化方法达到精确分析.文中给出了非线性网络响应的Volterra级数解的连续算式,为解决连续算式计算麻烦的问题,提出用方波脉冲技术处理用Volterra级数表示法描述的非线性网络响应与激励之间关系的一组广义卷积积分的迭加计算,从而得到非线性网络响应求解的Volterra级数解的离散算式.仿真表明该算法求出的非线性网络响应与真实模型曲线十分逼近,证明了它的有效性.     

弱非线性动态系统Volterra核自动测试系统的研究

本文讨论弱非线性动态系统Ｖｏｌｔｅｒｒａ核自动测试系统的研制，应用Ｖｏｌｔｅｒｒａ泛函级数和计算机技术于非线性系统，本文结合频率域多点测量弱非线性系统前二阶核的算法ＱＭＭＰ２及测量前三阶核的算法ＱＭＭＰ３，设计了自动测试系统。本文给出应用该系统的两个测量实例。     

MIMO非线性系统辨识：Volterra级数法

本文讨论了一般ＭＩＭＯ非线性系统的Ｖｏｌｔｅｒｒａ级数表示,给出并证明了Ｖｏｌｔｅｒｒａ核矩阵存在的条件。提出了两种辨识Ｖｏｌｔｅｒｒａ核矩阵的方法,即随机响应法与脉冲响应法。给出了利用系统的输入输出信号计算Ｖｏｌｔｅｒｒａ核矩阵的公式。最后,利用仿真实例验证上述方法的有效性。     

一种分析非线性振荡器频率及振幅灵敏度的新方法

本文提出了一种基于Volterra函数分析非线性振荡器频率及振幅灵敏度的新方法,该方法不仅克服了传统分析方法所受到的非线性元件应为弱非线性,非线性振荡幅度应足够小这两方面的限制,而且还可以用来分析高阶非线性振荡电路.本文对该方法进行了理论上的探讨.     

A mixed-domain method for identification of quadratically nonlinearsystems

A new mixed-domain method for identifying Volterra transfer functions of a nonlinear system, which can be represented by a second-order truncated Volterra series, is presented in this paper. This method is built on a discrete mixed-domain Volterra model derived from analyzing both discrete time- and frequency-domain Volterra models of quadratically nonlinear systems. It is shown that the conventional discrete frequency-domain Volterra model can be derived from the discrete mixed-domain Volterra model by making certain approximations. In this sense, the frequency-domain model can be considered to be a cough version of the mixed-domain model and thus cannot outperform the mixed-domain model in terms of modeling capability. In addition, the new method is shown to be able to properly identify the Volterra transfer functions even when the output of the quadratically nonlinear system is aliased. Based on this insight, a new anti-aliasing frequency-domain method, which is immune from the output aliasing problem, is developed. The superiority of these new methods over the conventional method is demonstrated by using them to analyze known quadratically nonlinear systems     

Indirect sliding mode control based on gray-box identification method for pneumatic artificial muscle

We present an indirect robust nonlinear controller for position-tracking control of a pneumatic artificial muscle (PAMs) testing system. The system modeling is reviewed, for which the existence of uncertain, unknown, and nonlinear terms in the internal dynamics is presented. From the obtained results, an online identification method is proposed for estimation of the internal functions with learning rules designed via a Lyapunov derivative function. A robust nonlinear controller is then designed based on the approximated functions to satisfy the control objective under the sliding mode technique. Appropriate selection of the smooth robust gain and the sliding surface ensures convergence of the tracking error to a desired level of performance. Stability of the closed-loop system is proven through another Lyapunov function. The proposed approach is verified and compared with a conventional proportional–integral–differential (PID) controller, adaptive recurrent neural network (ARNN) controller, and robust nonlinear controller in a real-time system with three different kinds of trajectories and loading. From the comparative experimental results, the effectiveness of the proposed method is confirmed with respect to transient response, steady-state behavior, and loading effect.     

Parametric Characteristic Analysis for Generalized Frequency Response Functions of Nonlinear Systems

In order to explicitly reveal the relationship between system frequency response functions and model parameters which define system nonlinearities, and consequently unveil a direct connection from model parameters to system frequency response characteristics, a parametric characteristic analysis approach is proposed for Volterra systems described by a nonlinear differential equation (NDE). The parametric characteristics of the generalized frequency response functions (GFRFs) for the NDE model are established, and some important properties are discussed, which can explicitly reveal what model parameters contribute and how these parameters affect the GFRFs. Based on the parametric characteristic analysis, it is demonstrated how the system frequency domain characteristics are related to the system time domain model parameters and how the output frequency response function can now be determined explicitly with a detailed polynomial structure. These new results provide a significant and novel insight into the analysis and design of nonlinear systems in the frequency domain. Several examples are included to illustrate the results.     

Spectral modeling of switched-mode power converters

A new modeling approach for the spectral analysis of pulsewidth modulated (PWM) converters with independent inputs is developed. The key of this approach is to extend the Volterra functional series to nonlinear systems with multiple independent inputs. After formulating the state-space equations describing the dynamical behavior of PWM converters, the Volterra transfer function characterizing the output frequency response can be obtained, which is then symmetrised to form the spectral model. Since the model is developed in a closed form, it is suitable for computer analysis. The modeling approach has been applied to various PWM converters, and the results are verified. The spectral models of different power converters can readily be obtained by using this general approach