Nonlinear black-box modeling in system identification: a unified overview

A nonlinear black-box structure for a dynamical system is a model structure that is prepared to describe virtually any nonlinear dynamics. There has been considerable recent interest in this area, with structures based on neural networks, radial basis networks, wavelet networks and hinging hyperplanes, as well as wavelet-transform-based methods and models based on fuzzy sets and fuzzy rules. This paper describes all these approaches in a common framework, from a user's perspective. It focuses on what are the common features in the different approaches, the choices that have to be made and what considerations are relevant for a successful system-identification application of these techniques. It is pointed out that the nonlinear structures can be seen as a concatenation of a mapping form observed data to a regression vector and a nonlinear mapping from the regressor space to the output space. These mappings are discussed separately. The latter mapping is usually formed as a basis function expansion. The basis functions are typically formed from one simple scalar function, which is modified in terms of scale and location. The expansion from the scalar argument to the regressor space is achieved by a radial- or a ridge-type approach. Basic techniques for estimating the parameters in the structures are criterion minimization, as well as two-step procedures, where first the relevant basis functions are determined, using data, and then a linear least-squares step to determine the coordinates of the function approximation. A particular problem is to deal with the large number of potentially necessary parameters. This is handled by making the number of ‘used’ parameters considerably less than the number of ‘offered’ parameters, by regularization, shrinking, pruning or regressor selection.     

电梯交通系统(Ⅰ)──电梯交通配置现状及发展

本文对国内外电梯交通配置设计现状及发展趋势作了论述。指出了由统计特性描述进入到采用专家系统和模糊规则的动态特性描述这一总的发展趋势。     

螺杆泵举升性能模糊综合评价

对螺杆泵举升性能的影响因素进行了综合分析，建立了螺杆泵举升性能综合评价的指标体系，并利用模糊数学方法确立了该系统的综合评价模型，将该模型应用于2台GLB500—12型螺杆泵，其评价结果与在实际工作中的产液量和寿命的综合指标基本吻合，从而验证了该方法的正确性，为螺杆泵举升性能的综合评价提供了一种有效方法。     

模糊技术的发展及在相关领域中的应用

本文介绍了模糊技术的发展和现状，以及在相关领域中的应用情况，并且讨论了模糊技术在我国的产业化方向等问题。     

利用模糊评判方法确定张东构造油藏储量计算的可靠程度

张巨河油田张东构造地处大港滩海交接处,海域部分探井少.目前用油藏描述方法计算的探明储量,其落实程度备受关注.储量落实程度的评价是一个多因素综合评判问题,而且这些因素还分属不同层次.模糊综合评判是应用较为广泛的模糊数学方法之一.该方法建立的综合评判涉及三个要素,即因素集、评判集和单因素评判,由此所构造的模糊评判关系是模糊综合评判的基础.本文用该方法对张东构造沙二段油藏的探明储量落实程度作了尝试性评价.     

A design and analysis of objective function-based unsupervised neural networks for fuzzy clustering

Fuzzy clustering has played an important role in solving many problems. In this paper, we design an unsupervised neural network model based on a fuzzy objective function, called OFUNN. The learning rule for the OFUNN model is a result of the formal derivation by the gradient descent method of a fuzzy objective function. The performance of the cluster analysis algorithm is often evaluated by counting the number of crisp clustering errors. However, the number of clustering errors alone is not a reliable and consistent measure for the performance of clustering, especially in the case of input data with fuzzy boundaries. We introduce two measures to evaluate the performance of the fuzzy clustering algorithm. The clustering results on three data sets, Iris data and two artificial data sets, are analyzed using the proposed measures. They show that OFUNN is very competitive in terms of speed and accuracy compared to the fuzzy c-means algorithm.     

EXTENSION OF THE RELATIONAL DATABASE AND ITS ALGEBRA WITH ROUGH SET TECHNIQUES

This paper describes a database model based on the original rough sets theory. Its rough relations permit the representation of a rough set of tuples not definable in terms of the elementary classes, except through use of lower and upper approximations. The rough relational database model also incorporates indiscernibility in the representation and in all the operators of the rough relational algebra. This indiscernibility is based strictly on equivalence classes which must be defined for every attribute domain. There are several obvious applications for which the rough relational database model can more accurately model an enterprise than does the standard relational model. These include systems involving ambiguous, imprecise, or uncertain data. Retrieval over mismatched domains caused by the merging of one or more applications can be facilitated by the use of indiscernibility, and naive system users can achieve greater recall with the rough relational database. In addition, applications inherently “rough” could be more easily implemented and maintained in the rough relational database.     

模糊自适应的高超飞行器控制与干扰

针对具有超大飞行马赫数、超宽飞行包络、飞行环境复杂等特点的高超声速飞行器,提出了基于模糊自适应的高超飞行器高度控制方法,分别设计了高度和速度控制器.针对所设计的控制器,分析了气动干扰力矩、测量噪声、舵机干扰、气动参数不确定性和飞行器模型参数不确定性对飞行器高度控制和速度控制效果的影响,然后又分析了综合考虑以上干扰和不确定性对飞行器高度控制和速度控制效果的影响.仿真结果表明,对各种干扰和不确定性,所设计的控制器速度和高度控制有较好的跟踪性和鲁棒性,达到了满意的效果.     

Adaptive fuzzy decentralized control for nonlinear large-scale systems based on high-gain observer

An adaptive fuzzy decentralized backstepping output-feedback control approach is proposed for a class of nonlinear large-scale systems with completely unknown functions,the interconnections mismatched in control inputs,and without the measurements of the states.Fuzzy logic systems are employed to approximate the unknown nonlinear functions,and an adaptive high-gain observer is developed to estimate the unmeasured states.Using the designed high-gain observer,and combining the fuzzy adaptive control theory with backstepping approach,an adaptive fuzzy decentralized backstepping output-feedback control scheme is developed.It is proved that the proposed control approach can guarantee that all the signals of the closed-loop system are semi-globally uniformly ultimately bounded(SUUB),and that the observer errors and the tracking errors converge to a small neighborhood of the origin by appropriate choice of the design parameters.Finally,a simulation example is provided to show the eectiveness of the proposed approach.     

基于模糊AHP的大学课堂教学质量评价研究

为了对大学教师课堂教学质量进行有效的监督和管理,建立了现代信息技术环境下大学教师课堂教学质量评价指标体系,基于模糊综合评判法和层次分析法(AHP)建立了教师课堂教学质量评价模型,应用此模型实例分析某教师的课堂教学质量并提出相应的提升策略,提高了评价的科学性和实用性。