基于TS模型的结构振动模糊控制方法

将TS模糊控制模型用于结构振动控制中,提出了一种新型的模糊控制器。利用传统LQR控制算法确定TS模糊控制器的参数,提出一种新的形成模糊控制规则的方法,克服了TS模糊控制器参数较多,规则难以确定的缺点;并结合一座三层钢框架模型,进行仿真分析,验证了提出的方法的有效性。     

基于动态模糊神经网络的结构主动控制仿真分析

在模糊控制中,如何更加合理地生成控制规则,是其应用的一个重要问题。本文采用动态模糊神经网络(DFNN)算法,并借助于最优控制算法的样本数据,实现建筑结构振动控制中的模糊规则自动提取。首先,介绍了DFNN的结构和算法;其次,采用DFNN算法设计了二输入单输出及四输入单输出两种模糊控制器,对顶层设置AMD控制装置的五层钢框架模型结构进行模糊控制仿真分析。仿真结果表明,两种模糊控制器对顶层位移和加速度反应峰值的控制效果达到50%和30%以上,对地震输入和结构参数的变化均具有较好的鲁棒性;相比二输入模糊控制器,四输入模糊控制器的控制效果更好。本文研究为地震作用下建筑结构AMD模糊控制提供了新的思路和方法。     

基于磁控形状记忆合金驱动器的结构自适应模糊控制

基于新型材料磁控形状记忆合金(MSMA)变形率大和反应迅速的特性,设计制作了一种磁控形状记忆合金主动杆件,将其应用到1个4层的空间杆系模型结构振动控制中;并结合遗传算法,对MSMA驱动器在模型结构中的布置进行优化。利用自适应模糊控制原理,建立了含多个调整因子的规则自调整模糊控制规则。然后对空间杆系结构进行规则自调整的结构模糊控制仿真,比较了El Centro地震波作用下结构在无控、模糊控制以及自适应模糊控制下的地震响应。仿真结果表明:MSMA驱动器具有良好的作动效应,经优化布置的MSMA驱动器能够有效的降低结构的振动响应;规则自调整的自适应模糊控制自适应性强,能够应用于结构的主动减振控制中。     

高层建筑横风向反应的模糊神经网络控制

介绍了第3代结构风振控制基准问题的定义。通过观测部分楼层加速度和控制力输出,建立了模糊神经网络控制器,解决了传统控制中有限的传感器数目对系统振动状态估计的困难;利用模糊神经网络预测结构的控制行为,消除了闭环控制系统中存在的时滞;通过模糊神经网络控制器的学习功能,解决了土木工程复杂结构模糊控制中难以依据专家的主观经验来确定模糊控制规则和语言变量隶属函数等困难。以风振控制的基准问题为研究对象,编制了程序对受控系统进行数值仿真分析。分析表明,模糊神经网络控制策略能有效地抑制高层建筑的风振反应。     

相邻建筑结构的模糊振动控制

本文研究了相邻建筑结构的模糊控制问题。首先,介绍相邻建筑结构体系的特点,建立体系的力学模型及运动方程;然后,进行了半主动控制研究,提出了控制的方法;最后,利用模糊控制方法实现了结构的智能控制。通过以上研究,说明相邻建筑结构相互振动控制是十分有效的,所得出的结论对实际工程的应用具有指导意义。     

海底管线悬空段模糊固有频率的计算

西文玉石窿海底管线管跨段两端点支撑土壤在涡激振动过程中的变形特性。在此基础上，提出了管跨涡激振动的力学模型；深入探讨了端点支撑的弹性系数和阻尼系数的模糊性。基于模糊推理规则，依据海底土壤力学特性参数与其影响因素间的模糊关系，提出了确定支撑土壤的弹性系数和阻尼系数的方法，并通过模型实验，验证了据此方法计算出的模糊固有频率。     

结构模糊控制规则优化生成的遗传算法

本文采用实数个体编码解码、两点交叉、两点变异、保留最优个体的模糊遗传算法对模糊控制规则进行优化;其次,对三层框架结构的模糊遗传算法控制进行了仿真实验,同时,与经验规则的模糊控制效果进行了比较;最后,对结构模糊遗传算法的鲁棒性进行了仿真试验,进一步验证了本文所提方法的可行性和有效性.     

建筑结构地震响应半主动控制的遗传-模糊算法

本文针对建筑结构地震响应半主动控制问题,应用基于遗传算法优化模糊规则库的遗传—模糊控制方法,通过MR阻尼器实现减小建筑结构地震响应。将结构的位移和加速度响应峰值控制双重指标作为目标函数,运用遗传算法的基本操作得到一组优化的模糊推理规则。以结构位移、加速度、地震加速度信号作为输入量,以MR阻尼器所提供的控制力为输出量,分别构造单阻尼器和多阻尼器的模糊控制策略。以某3层和6层框架结构为例,分别对两种遗传—模糊控制算法进行数值仿真分析,并与LQR最优控制结果进行比较。数值分析结果表明,采用遗传—模糊算法能够有效地减小结构的地震响应。     

基于遗传算法优化的高层建筑风振模糊控制

本文针对高层建筑风振控制问题,应用基于遗传算法优化模糊规则库的模糊控制方法,通过MR阻尼器实现减小高层建筑风振反应. 采用双输入、单输出的模糊控制策略, 即以风荷载和其变化率为输入量, 以MR阻尼器所提供的控制力为输出量.利用基于遗传算法的优化的模糊规则库,根据作用模糊子集的推理方法进行模糊推理运算, 并采用常用的重心法进行解模糊处理.以某12层框架结构为例, 进行数值模拟分析,并与优化前的模糊控制策略和LQR最优控制策略进行比较.数值分析结果表明,利用遗传算法使优化模糊规则库得以优化,改善了模糊控制的效果,有效地减小了结构的风振反应.     

基于模型参考的结构非线性自适应减振控制

本文针对非线性结构振动控制问题,提出了一种将线性二次型最优(LQR)控制算法和模糊控制算法相结合的自适应减震控制方法。以原线性结构,即名义系统作为参考模型,基于参考模型设计了LQR控制器,并利用遗传算法优化LQR控制器的加权系数;将结构振动中的非线性部分作为不确定参数,以此来设计模糊控制器,弥补了结构非线性部分对振动控制的影响。最后,通过钢筋混凝土非线性结构算例验证本文所提算法的有效性。结果表明:强震作用下,结构构件会产生屈服进入非线性阶段,而基于线性参考模型设计的LQR控制器并不适用于非线性结构;模糊控制器可以补偿结构非线性产生的影响,达到自适应减震控制的目的。     

Fuzzy sliding mode control for a building structure based on genetic algorithms

Based on the genetic algorithms (GAs), a fuzzy sliding mode control (FSMC) method for the building structure is designed in this research. When a fuzzy logic control method is used for a structural system, it is hard to get proper control rules directly, and to guarantee the stability and robustness of the fuzzy control system. Generally, the fuzzy controller combined with sliding mode control is applied, but there is still no criterion to reach an optimal design of the FSMC. In this paper, therefore, we design a fuzzy sliding mode controller for the building structure control system as an optimization problem and apply the optimal searching algorithms and GAs to find the optimal rules and membership functions of the FSMC. The proposed approach has the merit to determine the optimal structure and the inference rules of fuzzy sliding mode controller simultaneously. It is found that the building structure under the proposed control method could sustain in safety and stability when the system is subjected to external disturbances. Copyright © 2002 John Wiley & Sons, Ltd.     

Rule reduction in fuzzy logic for better interpretability in reservoir operation

Decision‐making in reservoir operation has become easy and understandable with the use of fuzzy logic models, which represent the knowledge in terms of interpretable linguistic rules. However, the improvement in interpretability with increase in number of fuzzy sets (‘low’, ‘high’, etc) comes with the disadvantage of increase in number of rules that are difficult to comprehend by decision makers. In this study, a clustering‐based novel approach is suggested to provide the operators with a limited number of most meaningful operating rules. A single triangular fuzzy set is adopted for different variables in each cluster, which are fine‐tuned with genetic algorithm (GA) to meet the desired objective. The results are compared with the multi fuzzy set fuzzy logic model through a case study in the Pilavakkal reservoir system in Tamilnadu State, India. The results obtained are highly encouraging with a smaller set of rules representing the actual fuzzy logic system. Copyright © 2007 John Wiley & Sons, Ltd.     

Semi‐active fuzzy control for seismic response reduction using magnetorheological dampers

A semi‐active fuzzy control strategy for seismic response reduction using a magnetorheological (MR) damper is presented. When a control method based on fuzzy set theory for a structure with a MR damper is used for vibration reduction of a structure, it has an inherent robustness, and easiness to treat the uncertainties of input data from the ground motion and structural vibration sensors, and the ability to handle the non‐linear behavior of the structure because there is no longer the need for an exact mathematical model of the structure. For a clipped‐optimal control algorithm, the command voltage of a MR damper is set at either zero or the maximum level. However, a semi‐active fuzzy control system has benefit to produce the required voltage to be input to the damper so that a desirable damper force can be produced and thus decrease the control force to reduce the structural response. Moreover, the proposed control strategy is fail‐safe in that the bounded‐input, bounded‐output stability of the controlled structure is guaranteed. The results of the numerical simulations show that the proposed semi‐active control system consisting of a fuzzy controller and a MR damper can be beneficial in reducing seismic responses of structures. Copyright © 2004 John Wiley & Sons, Ltd.     

结构振动的模糊状态控制法

本文介绍了一种模糊状态控制法,将结构的状态（即反应）进行模糊化,按照某种经验法则对结构反应进行控制。使用这种方法使得振动控制计算简便、控制直接和控制效果显著。     

RESPONSE ANALYSIS FOR FUZZY STOCHASTIC DYNAMICAL SYSTEMS WITH MULTIPLE DEGREES OF FREEDOM

Most real-life structural/mechanical systems have complex geometrical and material properties and operate under complex fuzzy environmental conditions. These systems are certainly subjected to fuzzy random excitations induced by the environment. For an analytical treatment of such a system subjected to fuzzy random excitations, it becomes necessary to establish the general theory of dynamic response of a system to fuzzy random excitations. In this paper, we extend the work published in Reference [1], and discuss the case of Multi-Degree-of-Freedom (MDF) fuzzy stochastic dynamical systems. The theory of the response, fuzzy mean response and fuzzy covariance response of multi-degree-of-freedom system to fuzzy random excitations in the time domain and frequency domain is put forward. Two cases to determine the fuzzy response statistics of the fuzzy stochastic dynamical system with multiple degrees of freedom are discussed. Two examples are considered in order to demonstrate the rationality and validity of the theory. © 1997 by John Wiley & Sons, Ltd.     

THE THEORY OF RESPONSE ANALYSIS OF FUZZY STOCHASTIC DYNAMICAL SYSTEMS WITH A SINGLE DEGREE OF FREEDOM

Most real-life structural/mechanical systems have complex geometrical and material properties and operate under complex fuzzy environmental conditions. These systems are certainly subjected to fuzzy random excitations induced by the environment. For an analytical treatment of such a system subjected to fuzzy random excitations, it becomes necessary to establish the general theory of dynamic response of a system to fuzzy random excitations. In this paper, the theory of response, fuzzy mean response and fuzzy covariance response of a single-degree-of-freedom (sdf) system to fuzzy random excitations in the time domain and frequency domain is put forward. The theory of response analysis of an sdf system to both stationary and non-stationary fuzzy random excitations in the time domain and frequency domain is established. Two examples are considered in order to demonstrate the rationality and validity of the theory, and the models of stationary filtered white noise and non-stationary filtered white noise fuzzy stochastic processes of the earthquake ground motion are set up. Methods of analysis for fuzzy random seismic response of sdf systems are put forward using the principles of response analysis of an sdf fuzzy random dynamic system.     

QANAT SYSTEMS IN IRAN

Abstract

A fuzzy rule-based technique is used for modelling the relationship between climatic forcing and droughts in a Central/Eastern European country, Hungary. Two types of climatic forcing'called premises'are considered: atmospheric circulation patterns (CP) and El Niño Southern Oscillation (ENSO). Both the Hess-Brezowsky CP types and ENSO events influence the occurrence of droughts, but the ENSO signal is relatively weak in a statistical sense. The fuzzy rule-based approach is able to learn the high space—time variability of monthly Palmer Drought Severity Index (PDSI) and results in a proper reproduction of the empirical frequency distributions. The “engine” of the approach, the fuzzy rules, are ascertained from a subset called the learning set of the observed time series of premises (monthly CP frequencies and Southern Oscillation Index) and PDSI response. Then an independent subset, the validation set, is used to check how the application of fuzzy rules reproduces the observed PDSI.     

A fuzzy logic based dynamic wave model inversion algorithm for canal regulation

A fuzzy logic based centralized control algorithm for irrigation canals is presented. Purpose of the algorithm is to control downstream discharge and water level of pools in the canal, by adjusting discharge release from the upstream end and gates settings. The algorithm is based on the dynamic wave model (Saint‐Venant equations) inversion in space, wherein the momentum equation is replaced by a fuzzy rule based model, while retaining the continuity equation in its complete form. The fuzzy rule based model is developed on fuzzification of a new mathematical model for wave velocity, the derivational details of which are given. The advantages of the fuzzy control algorithm, over other conventional control algorithms, are described. It is transparent and intuitive, and no linearizations of the governing equations are involved. Tuning of the algorithm and method of computation are explained. It is shown that the tuning is easy and the computations are straightforward. The algorithm provides stable, realistic and robust outputs. The disadvantage of the algorithm is reduced precision in its outputs due to the approximation inherent in the fuzzy logic. Feed back control logic is adopted to eliminate error caused by the system disturbances as well as error caused by the reduced precision in the outputs. The algorithm is tested by applying it to water level control problem in a fictitious canal with a single pool and also in a real canal with a series of pools. It is found that results obtained from the algorithm are comparable to those obtained from conventional control algorithms. Copyright © 2009 John Wiley & Sons, Ltd.