交通流模型参数的近似动态规划辨识方法

针对交通流模型的强非线性、不确定性等特点,提出了基于近似动态规划的交通流模型参数辨识算法.该算法具有自学习和自适应的特性,不依赖于被控对象的解析模型.严格的理论推导证明了这种参数辨识方案的收敛性,仿真结果验证了所提出算法的有效性.     

NOE TS fuzzy modelling of nonlinear dynamic systems with uncertainties using symbolic interval-valued data

An approach to Nonlinear Output Error (NOE) modelling using Takagi–Sugeno (TS) fuzzy model for a class of nonlinear dynamic systems having variability in their outputs is presented. Furthermore, the approach is compared and graphically illustrated with other alternate approaches on the basis of interval data and interval membership functions. Assuming the identification method can be repeated offline a number of times under similar conditions, multiple input–output time series can be obtained from the underlying system. These time series are pre-processed using the techniques of statistics and probability theory to generate the envelopes of response (curves outlining the upper and lower extremes of response) at each time instant. Two types of envelopes are described in this research: the max–min envelopes and the envelopes based on the confidence intervals provided by extended Chebyshev's inequality. By incorporating interval data in fuzzy modelling and using the theory of symbolic interval-valued data, a TS fuzzy model with interval antecedent and consequent parameters is obtained. This algorithm provides a model for predicting the expected response as well as envelopes. In order to validate the presented model, a simulation case study is devised in this paper. Moreover, it is demonstrated on the real data obtained from an electro-mechanical throttle valve.     

机动目标运动模型动态辨识理论的研究

在对现有机动目标假定模型结构的合理性及现代战场对目标模型需求性综合分析的基础上，完成了机动目标运动模型的辨识理论研究，提出了机动目标运动模型可动态辨识的条件．为解决机动目标运动模型动态辨识提供了新的技术途径．所提出的“参数辨识模型”具有良好的模型结构，对目标的各种运动模态具有广泛的适应能力．     

一种基于遗传算法与进化编程的系统辨识方法

分析比较了遗传算法（GA）和进化编码（EP）在解决系统辨识问题中的优劣，提出一种将GA和EP相结合的新的系统辨识方法，该方法既不依赖于种群的初始值，又具有较强的稳定性。仿真结果表明了该方法的有效性和独到之处。     

一种动态非线性模型传感器的辨识和补偿方法

针对利用Wiener模型表达的具有动态非线性的传感器进行系统辨识和性能补偿。将系统分解为动态非线性环节和静态线性环节,利用函数链人工神经网络和遗传算法分别进行系统辨识,通过静态非线性补偿将系统简化为线性系统,再进行动态性能补偿。利用LabVIEW设计虚拟仪器,经过仿真表明该方法是有效的。     

一种求解符号回归问题的粒子群优化算法

符号回归以构建一个能拟合给定数据集的函数模型为目的, 是对基本函数、运算符、变量等进行组合优化的过程.本文提出了一种求解符号回归问题的粒子群优化算法.算法以语法树对函数模型进行表达, 采用基因表达式将语法树编码为一个粒子, 设计了粒子的飞行方法及$r$-邻域环状拓扑的粒子学习关系.为使粒子具有跳出局部极值的能力和减轻粒子快速趋同对全局寻优造成的不利影响, 分别设计了突变算子和散开算子.此外, 为了得到比较简洁的函数模型, 在粒子的评价函数中以罚函数的方式对编码的有效长度进行控制.仿真实验表明, 提出的算法可以获得拟合精度更高、简洁性更好的函数模型.     

基于混合逻辑动态模型的混杂系统预测控制

针对过程工业控制对象的混杂特性，采用基于混合逻辑动态模型的预测控制策略。给出混杂系统的建模方法，并对其稳定性进行分析。仿真结果表明基于混合逻辑动态模型的预测控制能使混杂系统跟踪设定值并满足操作约束，为研究新一代复杂工业控制系统提供了新的思路。     

Assurance of dynamic adaptation in distributed systems

Long running applications often need to adapt due to changing requirements or changing environment. Typically, such an adaptation is performed by dynamically adding or removing components. In these type of adaptations, components are often added to or removed from multiple processes in the system. As a result, during adaptation, the system may consist of both changed and unchanged processes, causing old and new components to overlap. This overlapping of components during adaptation may induce cross-component communication, which may lead to behavior during adaptation that is unpredictable and/or undesirable.In this paper, we discuss an approach to model and verify overlap adaptation. We use the transitional-invariant lattice and the transitional-faultspan lattice to verify the correctness of adaptation in the absence and the presence of faults, respectively. We also discuss a framework to support implementation of overlap adaptation.     

Parameter identification for a traffic flow model

In this paper, a macroscopic model is presented which describes the traffic flow on a freeway by a set of nonlinear, deterministic difference equations. The model is deduced from simple physical and empirical considerations and contains a set of free parameters which have to be estimated using real traffic data. This identification procedure is formulated here as a parameter optimization problem which is solved by nonlinear programming. In addition, the sensitivity of the model with respect to parameter changes and structural changes is investigated. Although stochastic events play a role in traffic dynamics, the results demonstrate that the validated model copes surprisingly well with real traffic behaviour.     

New dynamic fuzzy structure and dynamic system identification

In this study, a new fuzzy system structure that reduces the number of inputs is proposed for dynamic system identification applications. Algebraic fuzzy systems have some disadvantages due to many inputs. As the number of inputs increase, the number of parameters in the training process increase and hence the classical fuzzy system becomes more complex. In the conventional fuzzy system structure, the past information of both inputs and outputs are also regarded as inputs for dynamic systems, therefore the number of inputs may not be manageable even for single input and single output systems. The new dynamic fuzzy system module (DFM) proposed here has only a single input and a single output. We have carried out identification simulations to test the proposed approach and shown that the DFM can successfully identify non-linear dynamic systems and it performs better than the classical fuzzy system.     

One-sided adaptation for infinite-horizon linear quadratic N -person non-zero-sum dynamic games and sensitivity analysis

In this paper, we consider a class of infinite-horizon discrete-time linear quadratic N-person games, in which one of the players lacks complete information about the game. With the assumptions of a perfect state information pattern and steady state feedback strategies, we convert the original game problem into a multivariable adaptive control problem by making use of the concept of fictitious play and the scheme of adaptive control. For the proposed adjustment procedure, we prove that each element of the estimates converges to its corresponding true value under the condition of persistent excitation. We also carry out a sensitivity analysis of performance indices with respect to the embedded unknowns by using multiple models.     

Discretization of continuous linear dynamic systems. Analysis of the methods

The problem of the discretization of continuous linear systems is considered. (A particular case is the problem of digital filter design for a given analog prototype.) Common and distinctive features of discrete systems, which are given by a number of different methods of discretization for one and the same continuous system, are analysed. The sampling period is assumed to be sufficiently small.     

支持硬件透明编程模型的动态可重构系统的设计与实现*

以Java作为可重构系统描述语言,提出了一种方法级的硬件透明编程模型,给出了硬件方法封装方式和软硬件方法动态链接过程。程序设计者调用软件方法进行应用开发,虚拟机根据软硬件划分结果动态加载并链接相应的硬件方法,从而达到简化编译器和综合工具以及屏蔽底层物理细节的目的。实验结果表明上述编程模型能够支持硬件透明编程,同时系统性能得到了明显的改善。     

遗传规划在符号回归中的应用

遗传规划(GP)是一种基于达尔文进化理论的数学规划方法。讨论了GP在符号回归中的应用。与传统的数据拟合方法相比,GP不必给出拟合函数的形式,同时,在初始群体足够大而且交叉和变异概率设置合理的情况下,不会陷入局部优化,具有更广泛的适用性。对于不给定函数形式的曲线拟合,GP可以自动得到曲线的函数形式及其参数大小,避免了传统方法的缺陷。通过具体的应用实例,说明了GP在测量数据处理中的应用。     

Automated Discovery of Numerical Approximation Formulae via Genetic Programming

This paper describes the use of genetic programming to perform automated discovery of numerical approximation formulae. We present results involving rediscovery of known approximations for Harmonic numbers, discovery of rational polynomial approximations for functions of one or more variables, and refinement of existing approximations through both approximation of their error function and incorporation of the approximation as a program tree in the initial GP population. Evolved rational polynomial approximations are compared to Padé approximations obtained through the Maple symbolic mathematics package. We find that approximations evolved by GP can be superior to Padé approximations given certain tradeoffs between approximation cost and accuracy, and that GP is able to evolve approximations in circumstances where the Padé approximation technique cannot be applied. We conclude that genetic programming is a powerful and effective approach that complements but does not replace existing techniques from numerical analysis.     

基于Elman神经网络的非线性动态系统辨识

研究了应用动态递归神经网络实现动态系统辨识的原理和方法,在没有被辨识对象的先验知识情况下,通过改进的Elman网络实现了非线性动态系统的辨识。仿真结果表明,与前馈网络相比,Elman网络具有学习速度快、泛化能力强的特点,可用较小的网络结构实现高阶系统的辨识,适用于具有本质非线性动态系统的辨识。     

Binaural source separation based on spatial cues and maximum likelihood model adaptation

This paper describes a system for separating multiple moving sound sources from two-channel recordings based on spatial cues and a model adaptation technique. We employ a statistical model of observed interaural level and phase differences, where maximum likelihood estimation of model parameters is achieved through an expectation-maximization algorithm. This model is used to partition spectrogram points into several clusters (one cluster per source) and generate spectrogram masks accordingly for isolating individual sound sources. We follow a maximum likelihood linear regression (MLLR) approach for tracking source relocations and adapting model parameters accordingly. The proposed algorithm is able to separate more sources than input channels, i.e. in the underdetermined setting. In simulated anechoic and reverberant environments with two and three speakers, the proposed model-adaptation algorithm yields more than 10 dB gain in signal-to-noise-ratio-improvement for azimuthal source relocations of 15° or more. Moreover, this performance gain is achievable with only 0.6 seconds of input mixture received after relocation.     

Nonlinear system identification using optimized dynamic neural network

In this paper, both off-line architecture optimization and on-line adaptation have been developed for a dynamic neural network (DNN) in nonlinear system identification. In the off-line architecture optimization, a new effective encoding scheme—Direct Matrix Mapping Encoding (DMME) method is proposed to represent the structure of neural network by establishing connection matrices. A series of GA operations are applied to the connection matrices to find the optimal number of neurons on each hidden layer and interconnection between two neighboring layers of DNN. The hybrid training is adopted to evolve the architecture, and to tune the weights and input delays of DNN by combining GA with the modified adaptation laws. The modified adaptation laws are subsequently used to tune the input time delays, weights and linear parameters in the optimized DNN-based model in on-line nonlinear system identification. The effectiveness of the architecture optimization and adaptation is extensively tested by means of two nonlinear system identification examples.     

以光合工厂理论为基础的微藻生长动力学模型的优化研究

以光合成工厂为思想基础的生长动力学模型是从机理上描述微藻光生化反应的一个重要模型,其模型的拟合程度关系到微藻浓度的准确预测。本文通过对实验数据进行合理分组,对其进行了进一步优化;另外,将管式反应器局部光强与光生长动力学相关联,建立了新的生长动力学模型。研究结果表明,优化后模型的判定系数明显增大,与局部光强相关且合理分组得到的数学模型与实验吻合程度最高,明显提高了微藻浓度预测的准确性。     

A novel model of adaptation decision-taking engine in multimedia adaptation

In heterogeneous environments, universal multimedia access (UMA) is proposed to provide multimedia content services. Multimedia adaptation is one of technologies to perform UMA, in which adaptation decision-taking engine (ADTE) is a key component. Though there are many models of ADTE existing, it needs to be reconsidered for personalized content services. In this paper, a novel model of ADTE is proposed based on decision tree termed adaptation decision tree (ADT) in which adaptation decision is viewed as sequence decision: modality decision and format decision. Correspondingly, user preferences are divided into two types: user modality preferences and user format preferences. By utilizing user preferences, the ADT model is built up. Before making decision, an optimal multimedia variation set (OMVS) with respect to user modality preferences is constructed and any element here is with the shortest distance to user format preferences for every modality. Therefore, adaptation decision can be executed by letting the element in OMVS travel along the ADT one by one. Finally, the first element that reaches the leaf with the logical value true is the decision result, or the one with the smallest value in distance is the decision variation if no elements get to proper leaf. Quantitative analysis and experimental simulation prove that the model is effective and efficient to cope with adaptation decision in multimedia adaptation especially in dynamic user preferences and resource-limited cases.