用互相关方法在线辨识线性多变量系统

至今为止,线性单变量系统的递推辨识已经有了许多有效的算法。相形之下,线性多变量系统的递推辨识有效算法要少的多。这些算法包括EL—Sherief和Sinha(1978)提出的递推最小二乘和随机逼近相结合的算法[1];Sinha和Kwong(1979)提出的广义最小二乘方法[2];Gauthier和Landau     

子系统为ARMA和分段线性函数的Wiener系统的参数辨识

本文研究ARMA线性子系统串联分段线性函数的Wiener系统的递推辨识问题.利用相关分析法和Yule-Walker方程给出线性部分参数的递推辨识算法,而对非线性部分参数用递推的最小二乘(LS)算法给出估计,并证明了这些算法都以概率1收敛到真值.     

变量带误差系统的递推辨识:从线性到非线性系统

介绍变量带误差(EIV)系统的递推辨识方法.在引言中扼要介绍了EIV系统辨识的现状后,分别对多变量线性EIV系统及EIV Hammerstein系统给出了递推辨识算法,并给出条件使这些估计以概率1收敛到真值.最后提出了一些值得进一步研究的问题.     

带衰减观测和随机传感器偏差的多传感器AR信号融合辨识与估计

研究了带衰减观测和随机传感器偏差的多传感器AR信号融合辨识与估计问题.首先,将AR模型转换为状态空间模型,将状态和传感器偏差进行增广得到一个等价的状态空间模型,给出了当系统模型精确已知下的最优滤波算法.然后,当AR信号参数、衰减观测随机变量的数学期望和方差未知时,提出了两段辨识算法.第一段采用递推增广最小二乘法(REL...     

基于主成份分析的递推子空间辨识

研究了多输入多输出系统的状态空间模型的递推子空间辨识问题.针对只有输出量测噪声的线性时不变系统,提出了基于随机逼近-主成份分析(SA-PCA)的估计扩张能观矩阵的递推算法.同时利用递推最小二乘在线估计系统矩阵.最后通过仿真例子说明算法的收敛速度和估计效果.     

Hénon混沌系统的模糊广义预测控制与同步

针对Hénon混沌系统,本文给出了一种基于T-S模糊模型的混沌系统广义预测控制算法。该方法将模糊辨识和广义预测控制结合起来应用到Hénon混沌系统中。首先,应用T-S模糊模型对Hénon混沌系统进行辨识,模糊聚类法辨识模型的前件参数,递推最小二乘法辨识结论参数。基于辨识模型,采用广义预测控制算法对其进行控制,实现了系统的跟踪与同步。仿真结果表明,与其它算法相比,该算法能够保证系统输出快速、有效地跟踪设定值。     

扩展截尾的随机逼近算法

注意到系统控制及相关领域中相当一类问题可归结为参数估计,而后者又可转化为未知函数的求根问题,首先介绍用带噪声量测递推地求根方法,即经典的随机逼近算法,并针对它的不足,引入扩展截尾的随机逼近算法(SAAWET),给出它的一般收敛定理.接着介绍应用SAAWET解决线性随机系统系数辨识及定阶, Hammerstein,Wiener,NARX等非线性系统的辨识,非线性随机系统的迭代学习控制及适应调节,以及其它一些问题.所给出的估计都是递推的,并且以概率1收敛到真值.     

动力学系统参数辨识问题最优控制解的理论与方法（II）—随机？…

基于（Ｉ）（《应用数学和力学》,１９９８,２０（２））的内容和随机最优控制理论,本首先介绍了随机动力学系统参数辨识问题最优控制解的概念。然后讨论了建立参数辨识问题ＨＪＢ方程的过程以及参数辨识的算法,最后给出了一个应用实例：解决动力学系统局部非线性参数辨识问题的方法。     

集值系统的辨识与适应控制

研究集值系统的辨识与适应控制,这是在随着网络化和信息化发展的过程中遇到的新兴热点问题.集值系统有着广泛的实际应用背景,但其研究才刚刚起步,主要原因是其辨识和控制的可用信息非常少,只是系统输出是否属于某个集合,从而使得已有方法无法适用.总结了近年来关于集值系统的研究工作:在辨识方面,从不同的系统结构、不同的噪声情况和不同的集值情形等方面进行了深入的研究.针对性地提出了参数解耦、比例满秩输入设计、联合可辨识、经验分布函数、在线递推等有效的辨识和控制方法,得到了一系列重要结果;在适应控制方面,实现了一类集值增益系统的适应跟踪控制.所得成果从正面回答了集值系统研究的核心科学问题:即使利用极为粗糙的集值信息,仍然可以精确地估计和控制系统,而且可以构造渐近最优的算法.     

基于全驱系统方法的冷带轧机压下系统自适应同步控制

由于冷带轧机操作侧与传动侧位置子系统的内部参数不确定性与不一致性,液压两侧位置系统的动态性能不同,这往往导致轧机生产的板材厚度不一致.文章基于全驱系统方法提出了一种参数自适应同步控制策略.首先,建立了液压位置系统的辨识模型与全驱模型;然后,基于辨识模型采用递推最小二乘算法对子系统的未知参数进行辨识;进而,针对建立的全驱同步系统模型,设计了参数化控制器,从而达到闭环系统稳定,以及两侧子系统的同步.最后,仿真结果表明了同步控制方案的有效性.     

一类非线性chemotaxis系统的局部零能控性

本文研究了一类非线性chemotaxis系统的能控性问题.利用这类线性化结合不动点的方法,获得了非线性系统的局部零能控性结果,推广了非线性抛物-椭圆型方程能控性的结果.     

Hierarchical multi-innovation stochastic gradient algorithm for Hammerstein nonlinear system modeling

This paper decomposes a Hammerstein nonlinear system into two subsystems, one containing the parameters of the linear dynamical block and the other containing the parameters of the nonlinear static block, and presents a hierarchical multi-innovation stochastic gradient identification algorithm for Hammerstein systems based on the hierarchical identification principle. The proposed algorithm is simple in principle and easy to implement on-line. A simulation example is provided to test the effectiveness of the proposed algorithm.     

FUZZY IDENTIFIER WITH EXPONENTIAL RATE OF CONVERGENCE FOR NONLINEAR DYNAMIC SYSTEMS

1 IntroductionIn recent yearst there is a development in the use of fuzzy systems for modelling, identifyingand controlling nonlinear systems. The reason is that conventional identification methods canonly use input-output pairs, but ignore linguistic information about the behavior of nonlinearsystems. Therefore, developing identifiers and controllers Of nonlinear systems which can com-bine both linguistic knowledge and numerical information is an important task. Ill this repect,works on the …     

ABSOLUTE STABILITY OF TIME-VARYING NONLINEAR CONTROL SYSTEM

In this paper the authors study two classes of time-varying nonlinear control systems. A few sufficient conditions of absolute stability of these systems were obtained by means of classical analysis and the analogue of the variation of constants formula of nonlinear systems. Moreover, they gave some sufficient conditions of absolute stability in Hurwitz angle for these systems.     

一类非最小相位非线性系统的鲁棒输出调节

研究了一类具有非最小相位和非线性外部系统的非线性系统的全局鲁棒输出调节问题.首先,利用浸入系统设计了一个非线性内模.其次,把原系统的全局鲁棒输出调节问题转化为增广系统的全局鲁棒镇定问题.然后,利用改变能量函数和动态增益技巧设计了一个状态反馈控制器,使得闭环系统的解有界并且跟踪误差渐近趋于零.最后,利用仿真结果验证了所设计的控制器的有效性.     

Optimal input system identification for nonlinear dynamic systems

The estimation accuracy for nonlinear dynamic system identification is known to be maximized by the use of optimal inputs. Few examples of the design of optimal inputs for nonlinear dynamic systems are given in the literature, however. The performance criterion is selected such that the sensitivity of the measured state variables to the unknown parameters is maximized. The application of Pontryagin's maximum principle yields a nonlinear two-point boundary-value problem. In this paper, the boundary-value problem for a simple nonlinear example is solved using two different methods, the method of quasilinearization and the Newton-Raphson method. The estimation accuracy is discussed in terms of the Cramer-Rao lower bound.     

非线性动力学系统的辨识：时频滤波与骨架曲线

利用非平稳信号的时频分析方法研究了一类非线性系统的频率特性和阻尼特性随运动形态的变化规律,得到了能简洁、直观地反映系统基本非线性动力学特性的广义骨架线性系统（简称GSLS）和骨架曲线。在此基础上,利用时频滤波方法根据系统非平稳响应信号对非线性系统进行辨识。该项工作为非线性系统反问题的研究提供了一条新的途径。     

Model Selection of Dnamical Systems via Entropic Regression and Bayesian Information Criteria

Recovering system model from noisy data is a key challenge in the analysis of dynamical systems. Based on a data-driven identification approach, we develop a model selection algorithm called Entropy Regression Bayesian Information Criterion (ER-BIC). First, the entropy regression identification algorithm (ER) is used to obtain candidate models that are close to the Pareto optimum and combine as a library of candidate models. Second, BIC score in the candidate models library is calculated using the Bayesian information criterion (BIC) and ranked from smallest to largest. Third, the model with the smallest BIC score is selected as the one we need to optimize. Finally, the ER-BIC algorithm is applied to several classical dynamical systems, including one-dimensional polynomial and RC circuit systems, two-dimensional Duffing and classical ODE systems, three-dimensional Lorenz 63 and Lorenz 84 systems. The results show that the new algorithm accurately identifies the system model under noise and time variable $t$, laying the foundation for nonlinear analysis.     

非线性灰色离散系统零解的稳定性

本文用区间矩阵和Ｌｙａｐｕｎｏｖ第二方法讨论了具有非线性扰动项的灰色离散系统的稳定性，得到了若干稳定性的代数判据，这些结果将文（５）的主要结果由线性推广到了非线性，并给出了实现的例子。     

Fault identification in nonlinear hybrid systems

The problem of fault identification in hybrid systems is investigated. It is assumed that the hybrid systems under consideration consist of a finite automaton, the set of nonlinear differential equations, and so-called mode activator that coordinates the action of these two parts. To solve the fault identification problem, sliding mode observers are used. The suggested approach for constructing sliding mode observers is based on the reduced order model of the original system. This allows to reduce complexity of sliding mode observers and relax the limitations imposed on the original system. Examples illustrate details of the solution.