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。     

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。     

MR阻尼器对桅杆结构风振响应的智能半主动控制

本文基于修正的拉格朗日坐标描述法，推导了空间四节点纤绳单元的大位移刚度矩阵的具体表达式。在将桅杆结构离散为空间四节点纤绳单元和梁单元的计算模型的基础上，建立了桅杆结构非线性风振响应分析的有限元方法。根据瞬时最优主动控制的原则，提出了MR阻尼器对桅杆结构风振反应智能半主动控制基于阻尼器位移的“开关—耗能”半主动控制策略。算例结果表明MR阻尼器能有效地减小桅杆结构的风振反应。     

巨子有控结构体系非线性地震响应的半主动控制

巨子有控结构体系(MSCSS)是一种具有自控能力的新型结构体系。本研究将磁流变(MR)阻尼器与MSCSS的工作机理相结合,采用模糊神经网络建立MR阻尼器的控制规则,利用遗传算法对模糊神经网络结构进行优化,在考虑构件发生非线性变形的情况下,研究了不同场地地震作用时的MSCSS非线性振动响应控制效果。通过与被动控制工况和以LQR算法为基础的半主动控制工况进行时域、频域范围内的对比研究,结果表明本文设计的模糊神经网络算法可以有效减小MSCSS的地震响应,并且在结构构件进入非线性状态以后仍然保持良好的稳定性,大大提高了结构的抗震性能。     

磁流变阻尼器对高层建筑风振反应的半主动控制

本文探讨了磁流变阻尼器在高层建筑风振控制中的应用，在经典线性最优控制理论的基础上，根据磁流变阻尼器的特点，提出了一种新型的半主动控制策略，应有该方法对一40层的钢结构的风振反应进行了计算机模拟，结果表明，采用磁流变阻尼器对高层建筑进行半主动控制的能够有效减小结构的风振反应。     

带裙房高层建筑地震反应控制振动台试验研究

2002年9月在香港理工大学成功地进行了带裙房高层建筑地震反应控制试验研究。设计和制作的结构模型是带3层裙房的12层高楼剪切模型,在裙房顶层与主楼之间安装单MR阻尼器形成MR阻尼器耦联结构模型。MR阻尼器采用美国LORD公司摩擦型MR阻尼器,并且选用其配套产品计算机电流控制器对其进行控制,控制系统采用德国dSPACE公司实时控制系统。对独立主楼、独立裙房和原结构模型的动力特性进行了辨识;对结构模型进行了El Centro地震动作用下的地震反应振动台试验;以作者提出的MR阻尼器半主动逻辑控制算法,对MR阻尼器耦联的结构模型进行了地震反应振动台试验。试验结果表明：用MR阻尼器耦联主楼与裙房,采用半主动逻辑控制方法进行控制,能有效抑制主楼的鞭梢效应并使主楼和裙房的地震反应减小。     

屋盖MR智能隔震系统对升船结构顶部厂房地震鞭梢效应的模糊控制

基于抑制升船结构顶部厂房地震鞭梢效应的目的，本文提出了升船结构顶部厂房屋盖MR智能隔震模糊控制的思想。文中，在建立屋盖智能隔震升船结构计算力学模型的基础上，建立了屋盖MR智能隔震系统对升船结构顶部厂房地震反应模糊控制的设计计算方法。文中并以中国某大坝巨型升船结构为背景，设计了屋盖MR智能隔震系统对升船结构顶部厂房地震反应模糊控制的控制系统。仿真分析和对MR阻尼器的参数研究表明，安装合适的屋盖MR智能隔震系统并采用模糊控制策略能有效地抑制具有不确定参数升船结构顶部厂房地震反应的鞭梢效应，且模糊控制器能保持较好的稳定性能。     

ER／MR智能阻尼器耦联的带裙房高层建筑结构地震反应的半主动控制

本文建立了用ER／MR智能阻尼器耦联的带裙房高层建筑结构地震反应半主动控制的设计计算方法,文中,在导出ER／MR智能阻尼器力学模型的基础上,建立了ER／MR智能阻尼器耦联的带裙房层建筑结构地震反应的基本方程,并根据瞬时最优主动控制的原则,提出了ER／MR智能阻尼器耦联的带裙房高层建筑地震反应半主动控制的基于最优主动控制位移的“开关－耗能”半主动控制策略,应用本文方法对主楼20层,裙房5层的计算结构;受控地震反应的模拟计算结构表明,耦联主楼和裙房的半主动的ER／MR智能阻尼器可有效地抑制带裙房高层建筑结构地震反应的鞭梢效应,并可均匀地减小结构各层的震反应,是一种简单,方便和有效的智能控制装置。     

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.     

混沌遗传算法在高层结构风振控制优化中的应用研究

将混沌遗传算法(Chaos Genetic Algorithm,简称CGA)引入高层结构的风振控制优化中,对采用黏弹性阻尼器来控制风振响应的高层结构进行参数优化;用Matlab语言编制了均布法、迭代法、简单遗传算法(Simple Genetic Algorithm,简称SGA)和混沌遗传算法的风振控制优化分析程序;对9个高层结构进行风振控制优化,对比了算法程序的计算效率以及无控、均布、迭代、SGA和CGA工况下的结构风振响应。研究结果表明:混沌遗传算法可以应用于高层结构风振控制优化之中;混沌遗传算法的计算效率比简单遗传算法最高提升了29%;经混沌遗传算法优化后,黏弹性阻尼器附加给结构的附加阻尼比与均布和迭代相比最高分别提高了61%和22%,CGA工况的顶层加速度响应与均布和迭代法相比最高分别减小了14%和12%。为高层结构风振控制优化研究提供了新思路,具有一定的理论价值和实际意义。     

结构振动的模糊建模与模糊控制规则提取

模糊振动控制中存在的模糊控制规则的建立大都依赖于主观经验的现状。对此本文提出了一种通过对结构振动模糊建模来产生控制规则的方法。首先，通过对系统运动状态变量的模糊化，建立结构振动的模糊关系模型；其次通过对结构振动的模糊关系模型的分析，提取出模糊控制规则；最后，通过一个单自由度体系的数值仿真方法进行了验证。     

Fuzzy control of piezoelectric friction dampers for seismic protection of smart base isolated buildings

This study proposes two fuzzy logic controllers (FLCs) for operating control force of piezoelectric friction dampers used for seismic protection of base-isolated buildings against various types of earthquake excitations. The first controller employs a hierarchic control strategy in which a higher-level supervisory controller operates a single sub-level FLC by modifying its input normalization factors in order to determine command voltage of the damper according to current level of ground motion. The second controller is a self organizing FLC that employs genetic algorithms in order to build a knowledge base for the fuzzy controller. Numerical simulations of a base-isolated building are conducted to evaluate the performance of the controllers. For comparison purposes, an optimal controller is also developed and considered in the simulations together with maximum passive operation of the friction damper. Results for several historical ground motions show that developed fuzzy logic controllers can effectively reduce isolation system deformations without the loss of potential advantages of seismic base isolation.     

Adaptive neuro-fuzzy evaluation of wind farm power production as function of wind speed and direction

Wind velocity assumes a critical part for measuring the power created by the wind turbines. Nonetheless, power production from wind has a few weaknesses. One significant issue is that wind is a discontinuous energy source which implies that there exists substantial variability in the generation of vigor because of different variables, for example, wind speed. Wind direction is a significant variable for proficient turbine control for getting the most energy with a given wind speed. Taking into account the conjectures on wind heading, it might be conceivable to adjust the turbine to the wind bearing to get the most energy yield. Since both forecasts of wind speed and direction are basic for effective wind energy collecting it is crucial to develop a methodology for estimation of wind speed and direction and afterwards to estimate wind farm power production as function of wind pace and heading distribution. Despite the fact that various numerical functions have been proposed for demonstrating the wind speed and direction frequency distribution, there are still disadvantages of the models like very demanding in terms of calculation time. In this investigation adaptive neuro-fuzzy inference system (ANFIS), which is a particular sort of the artificial neural networks (ANN) family, was used to anticipate the wind speed and direction frequency dispersion. Thereafter, the ANFIS system was utilized to gauge wind homestead power creation as function of wind velocity and bearing. Neural system in ANFIS modifies parameters of enrollment capacity in the fuzzy logic of the fuzzy inference system. The reenactment outcomes exhibited in this paper demonstrate the adequacy of the created technique.     

工程结构地震响应模糊半主动控制

提出了使用MR阻尼器（Magnetorheological Damper）作为控制设备,模糊集为基础的半主动控制算法,并运用提出的算法对土木工程结构地震响应进行了振动控制分析.本文方法的优势在于算法自身的鲁棒性、处理非线性问题的能力和不需要结构的精确数学模型,算法需要的输入变量少,可以解决实际工程中结构响应信息难以测量的困难.模糊算法的输出直接控制MR阻尼器的输入电压,控制器的计算非常简单且易于在工程中实现.本文以一个3层框架结构为算例,分析了本文算法与前人研究算法的异同.数值结果表明,本文提出的模糊半主动控制具有较高的效率,可以减小需要的控制力,充分使用了MR阻尼器的输入电压可以调节的功能,使MR阻尼器的功能得到了更好的发挥.     

Sliding mode fuzzy control: Theory and verification on a benchmark structure

A sliding mode fuzzy control (SMFC) algorithm is presented for vibration reduction of large structures. The rule base of the fuzzy inference engine is constructed based on the sliding mode control, which is one of the non‐linear control algorithms. In general, fuzziness of the controller makes the control system robust against the uncertainties in the system parameters and the input excitation, and the non‐linearity of the control rule makes the controller more effective than linear controllers. For verification of the present algorithm, a numerical study is carried out on the benchmark problem initiated by the ASCE Committee on Structural Control. To achieve a high level of realism, various aspects are considered such as actuator–structure interaction, sensor noise, actuator time delay, precision of the A/D and D/A converters, magnitude of control force, and order of control model. Performance of the SMFC is examined in comparison with those of other control algorithms such as H_{mixed 2/∞}, optimal polynomial control, neural networks control, and SMC, which were reported by other researchers. The results indicate that the present SMFC is efficient and attractive, since the vibration responses of the structure can be reduced very effectively and the design procedure is simple and convenient. Copyright © 2000 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.     

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.     

高架桥梁地震响应模糊半主动控制

提出了使用MR阻尼器（Magnetorheological Damper）作为控制设备，以模糊集为基础的半主动控制算法，研究了8种模糊控制规则在高架桥梁地震响应中的控制效果。本文提出的模糊方法的优势在于算法自身的鲁棒性、处理非线性问题的能力和不需要结构的精确数学模型，算法需要的输入变量少，模糊算法的输出直接控制MR阻尼器的输入电压，与LQR-clipped算法不同，MR阻尼器的输入电压可以是零与最大值之间的任意值。根据高架桥梁的结构特点，将典型的墩-支座-桥面结构简化为一个两自由度的线性系统，计算了El Centro地震激励下，MR模糊半主动控制的地震响应，并分别与没有控制及其他控制时的地震响应进行了对比，分析了各种控制算法的控制效果。研究结果表明，MR模糊半主动控制算法可以达到LQR-clipped半主动的控制效果，且模糊控制所需要的控制力较小，为有效地发挥MR阻尼器的功能提供了一种简单的半主动算法。     

Sub‐optimal control of structures

It is well known that the classical optimal control method requires all the state variables of the controlled system to be measurable and available for control feedback. However, for a high‐order or complex system some state variables are possibly unmeasurable in practice. In addition, the control cost will be higher if more sensors are used, because it is expensive to install sensors. On the other hand, when using the optimal control method with full‐state feedback, some state variables in control feedback have only a small effect on control performance. Neglecting these state variables does not affect the control performance greatly. Good control effectiveness can be obtained by using only the state variables that have a big effect on the control performance. So the questions become how to determine those state variables which have a big effect on the control performance? and how to design the optimal controller using only the determined state variables? The discrete sub‐optimal control method with partial‐state feedback is investigated in this paper. Firstly, the continuous control system and performance index are both transformed into discrete forms. Then the state variables, which have a big effect on the control performance, are determined using the second‐order sensitivity which is the second‐order derivative of the performance index with respect to control gain. The sub‐optimal controller is finally designed using only the determined state variables. Numerical examples are worked out to demonstrate the application of the proposed control algorithm. It is shown that the relative importance of each state variable can be indicated clearly by the second‐order sensitivity. The sub‐optimal control method presented is effective in reducing maximum responses of the structure. Copyright © 2003 John Wiley & Sons, Ltd.