地震作用下结构振动保性能鲁棒H2/H∞控制

针对建筑结构振动控制模型的不确定性,研究了被控建筑结构模型参数不确定性时的保性能鲁棒混合H2/H∞控制问题.将结构模型参数不确定性引入到被控结构状态方程的摄动矩阵之中,基于线性矩阵不等式设计了多目标保性能鲁棒混合H2/H∞鲁棒控制器.该控制器在规定的模型参数变化范围内,使得闭环控制系统同时满足H∞干扰抑制和最优H2性能.最后,以一个缩尺的多层剪切型建筑结构模型为例,给出了保性能鲁棒混合H2/H∞控制问题的设计过程,验证所提控制方法的有效性.数值分析结果表明,所提出的保性能鲁棒混合H2/H∞控制方法的控制效果明显,能有效地减小结构的地震峰值响应,且控制系统对结构参数不确定性有很强的鲁棒性.     

不确定组合系统的分散鲁棒局部最优控制

针对一类特殊结构的弱交联组合大系统，利用局部状态反馈通过对两个孤立子系统的最优化使整个系统是鲁棒稳定的．在这里不确定性是时变的，同时出现在子系统内部和交联项中，它们的统计信息并不知道，但它们的界限是可以获得的．     

切换双机电力系统的鲁棒控制器设计

研究了切换双机电力系统的鲁棒控制器设计问题.首先,考虑到实际系统中的不确定性对系统性能的影响,建立了切换双机电力系统含有不确定性的数学模型.然后,利用公共Lyapunov函数方法,给出了系统控制器的设计方案,并证明了闭环系统是稳定的.最后,总结了本文的工作并指出了今后将进一步探索的问题.     

结构不确定时滞组合系统的分散鲁棒稳定化

研究了一类具有结构不确定性线性时滞组合系统的分散鲁棒稳定化问题．文中利用比较原理，给出一种与时滞常数有关的通过分散无记忆状态反馈，使不确定组合系统渐近稳定的充分条件．     

考虑负荷不确定性的分布式能源系统鲁棒优化

针对分布式能源系统的经济效益有可能因实际负荷的不确定性无法充分发挥的问题,将考虑设备容量离散性的优化配置方法与最小最大后悔值法相结合,发展了考虑负荷不确定性的鲁棒优化配置方法.基于此方法,结合实例,采用由微型燃气轮机冷热电三联供和地下水地源热泵组成的分布式能源系统形式,研究负荷不确定性对系统配置和经济性的影响.考虑负荷不确定性有可能改变系统的优化配置容量、设备总造价及年总费用的最大后悔值,并降低系统优化配置方案在实际运行时的经济风险,使其经济效益更具鲁棒性.该实例研究验证了该方法的有效性.     

鲁棒控制在结构风振中的应用研究

针对结构的参数不确定性和结构的模型误差,将鲁棒控制理论引入结构控制中,提出了一种设计鲁棒控制器的简便方法。在高层建筑结构的风振控制中应用文中所提供的方法能产生良好的控制效果,具有较强的鲁棒性。     

不确定动态系统的离散反馈控制器的设计

介绍一种用于不确定性的连续线性系统的离散控制器设计方法 ,通过适当选择状态权矩阵和控制权矩阵来构造李雅谱诺夫函数 ,以获得能够确保闭环系统稳定的反馈控制规律 .当选择出适当的权矩阵后 ,则可直接得到鲁棒离散控制器 ,最后给出一实例说明该方法的实用性     

不确定中立型随机多时滞系统的鲁棒镇定

针对具有参数不确定性的中立型随机多时滞系统,讨论了鲁棒镇定问题,其中状态反馈控制器具有分布时滞.基于Lyapunov方法,由Ito公式,并利用Schur补原理,获得了用线性矩阵不等式表示的保证闭环系统随机均方稳定的时滞相关的充分条件.通过求解线性矩阵不等式,得出了随机时滞系统的具有分布时滞的状态反馈H∞控制器.最后,用例子说明了结果的有效性.     

室内散热器供热系统的鲁棒控制北大核心

建立了由散热器、阀门、室内空气和围护结构动态模型构成的室内散热器供热系统动态模型,分析了散热器供热系统的稳态与动态特性,提出了鲁棒H_∞控制器和鲁棒PI控制器的设计方法,对比分析了这2种控制器的扰动抑制性能。结果表明,这2种控制器都能提高室内供热系统的扰动抑制效果,但鲁棒H_∞控制器在稳定性、控制速度、控制精度上都优于鲁棒PI控制器。     

室内散热器供热系统的鲁棒控制

建立了由散热器、阀门、室内空气和围护结构动态模型构成的室内散热器供热系统动态模型,分析了散热器供热系统的稳态与动态特性,提出了鲁棒H_∞控制器和鲁棒PI控制器的设计方法,对比分析了这2种控制器的扰动抑制性能。结果表明,这2种控制器都能提高室内供热系统的扰动抑制效果,但鲁棒H_∞控制器在稳定性、控制速度、控制精度上都优于鲁棒PI控制器。     

Decentralized Parametric Damage Detection Based on Neural Networks

In this paper, based on the concept of decentralized information structures and artificial neural networks, a decentralized parametric identification method for damage detection of structures with multi-degrees-of-freedom (MDOF) is conducted. First, a decentralized approach is presented for damage detection of substructures of an MDOF structure system by using neural networks. The displacement and velocity measurements from a substructure of a healthy structure system and the restoring force corresponding to this substructure are used to train the decentralized detection neural networks for the purpose of identifying the corresponding substructure. By using the trained decentralized detection neural networks, the difference of the interstory restoring force between the damaged substructures and the undamaged substructures can be calculated. An evaluation index, that is, relative root mean square (RRMS) error, is presented to evaluate the condition of each substructure for the purpose of health monitoring. Although neural networks have been widely used for nonparametric identification, in this paper, the decentralized parametric evaluation neural networks for substructures are trained for parametric identification. Based on the trained decentralized parametric evaluation neural networks and the RRMS error of substructures, the structural parameter of stiffness of each subsystem can be forecast with high accuracy. The effectiveness of the decentralized parametric identification is evaluated through numerical simulations. It is shown that the decentralized parametric evaluation method has the potential of being a practical tool for a damage detection methodology applied to structure-unknown smart civil structures.     

Agent-based system identification for control-oriented building models

The paper presents a general agent-based system identification framework as potential solution for data-driven models of building systems that can be developed and integrated with improved efficiency, flexibility and scalability, compared to centralized approaches. The proposed method introduces building sub-system agents, which are optimized independently, by solving locally a maximum likelihood estimation problem. Several models are considered for the sub-system agents and a systematic selection approach is established considering the root mean square error, the parameter sensitivity to output trajectory and the parameter correlation. The final model is integrated from selected models for each agent. Two different approaches are developed for the integration; the negotiated-shared parameter model, which is a distributed method, and the free-shared parameter model based on a decentralized method. The results from a case-study for a high performance building indicate that the model prediction accuracy of the new approach is fairly good for implementation in predictive control.     

基于自适应RBF神经网络算法的建筑结构递阶分散控制研究

针对建筑结构振动控制的递阶分散控制问题进行研究。首先,通过设置全局控制器消除子系统间的关联耦合;在此基础上,结合Lyapunov稳定性理论和RBF神经网络理论设计了仅依赖于子系统位移和速度响应反馈信息的自适应控制律,并利用差分进化（DE）算法对自适应RBF神经网络局部子控制器相关参数进行优化,建立了适用于建筑结构振动控制的自适应RBF神经网络递阶分散控制（ARBFHDC）算法。对ASCE 9层Benchmark模型进行递阶分散控制设计、优化及仿真分析。结果表明,不同地震激励下,基于ARBFHDC算法设计的递阶分散控制较传统集中控制而言有更好的控制效果,且能保障各子系统作动器处于最大功效工作状态。     

Decentralized robust control of building structures based on sliding mode theory

In this paper, a decentralized control algorithm is proposed for actively controlling the response of the flexible tall building structures under earthquake excitations. In the proposed approach, tall building structure was divided into some substructures in the form of state equation. The interaction of the subsystems and external excitations is conducted as bounded generalized force acting on the subsystems. A decentralized control algorithm of tall building structures is established based on the sliding model control theory. The control structure is described based on unit vector control. The control law consists of two parts: a linear control law u_L and a nonlinear law u_N. The linear control is merely a linear state feedback controller, whereas the nonlinear feedback controller incorporates the discontinuous or continuous nonlinear elements of the control law. Using the advantage of match conditions of sliding mode theory and the bounded feature of generalized force, the overall stability of decentralized control is also investigated. The actuator arrangement and matching conditions are discussed. The effectiveness of the proposed method is demonstrated by the numerical simulation of the decentralized control of a 20-story benchmark structure under seismic excitations.     

自适应模糊PID控制器的研究

除了开／关控制,常规PID控制器是HVAC系统现场控制中应用最为广泛最基本的控制器,但对于非线性、时变的系统,常规的PID控制则很难达到满意的控制效果。本文提出了自适应模糊PID控制器模型,可以根据系统误差和误差变化率不断对PID控制器的输出进行在线调整。以某空调房间温度控制系统为研究对象,对自适应模糊PID控制器和常规PID控制器进行了对比。计算结果表明,自适应模糊PID控制器具有良好的动、静态性能,并且鲁棒性较强。     

Robust control of civil structures with parametric uncertainties through D‐K iteration

Active control is an alternative method to suppress the civil structural vibration, which is more effective than the passive control or strengthening the structural components. The performance of active control is dependent on the control strategy and the accuracy of the structural model. However, there always exist some uncertainties in the model, such as mass, damping and stiffness uncertainties. This paper presents a robust H_∞ controller design for civil structures with consideration of the parametric uncertainties. The formulation to extract the parametric uncertainties from the structural model matrices is proposed through the linear fractional transformations approach. The robust H_∞ controller design for the civil structures with the parametric uncertainties is achieved through the D‐K iteration method. The linear matrix inequality is then used in the H_∞ optimization procedure of the D‐K iteration. The robustness of the controller is first numerically validated by a four‐story building example and then experimentally corroborated by a shaking table test of a two‐story frame with one active mass damper. The results show that the robust H_∞ controller can consider the parametric uncertainties in the civil structural model and achieve the robust performance. Copyright © 2015 John Wiley & Sons, Ltd.     

Resilient urban drainage – Options of an optimized area-management

There is a need for an integrated approach for all involved stakeholders to adapt urban infrastructures to climate change effects and to take into account uncertainties of future developments. By integrating all relevant planning disciplines, a first step towards implementation of resilient technical and social infrastructures can be achieved. With the major goal of optimizing area-management as part of water sensitive urban design, the water sector and its area requirements build the main focus of this study. After identifying local flood hazards and potential surficial retention areas, the additional usage of decentralized stormwater management facilities for flood protection is tested in selected sectors. The results of the study confirm that the combined usage of decentralized facilities for pluvial flooding is a first step to protect urban infrastructure. It shows that decentralized facilities are more flexible than centralized facilities and, thus, have a higher adaptation capacity which is needed considering the various effects of climate change.     

地震作用下建筑结构的分散控制研究

对地震作用下建筑结构的振动控制方法进行研究,指出传统的集中控制策略在高层结构控制器设计中的局限性,阐述采用分散控制策略进行控制器设计的必要性及适用性.基于经典最优控制算法原理,导出两种分散控制算法--分散次优控制(Decentralized Sub-Optimal Control,DSOC)算法及分散经典最优控制(Decentralized Classic 0Dtimal Control,DCOC)算法.引入多市场概念,提出基于多市场机制的控制(Multi-Market Based Control,MMBC)算法并应用于高层结构分散控制中.对一高层受控结构进行数值计算与分析,结果表明采用分散控制策略与集中控制策略一样能有效地抑制结构振动反应,相对于集中控制的单一失效分散控制使系统的可靠性更强;显示MMBC算法较DSOC与DCOC算法具有参数选取简便、控制效果显著等优点,能较好地适用于高层结构分散控制器设计.     

Sensitivity analysis of vertically loaded pile reliability

The purpose of this paper is to examine the influence of geotechnical uncertainties on the reliability of vertically loaded pile foundations and the use of this information in decision-making support, especially when gathering the information necessary for reliability analyses. Two case studies of single pile foundations were selected, and each uncertainty source was investigated to identify which are the most important and influential in the evaluation of vertical pile resistance under axial loading. Reliability sensitivity analyses were conducted using FORM (the first-order reliability method) and MCS (Monte Carlo simulations). The characterisation of uncertainties is not an easy task in geotechnical engineering. The aim of the analyses described in this paper is to optimise resources and investments in the investigation of the variables in pile reliability. The physical uncertainties of actions, the inherent variability of soil and model error were assessed by experimental in situ standard penetration tests (SPT) or from information available in the literature. For the cases studied, the sensitivity analysis results show that, in spite of the high variability of the soils involved, model error also plays a very important role in geotechnical pile reliability and was considerably more important than soil variability in both case studies. From a comparison of the two reliability methods (FORM and MCS), it was concluded that FORM is applicable in simple cases and as a first approach because it is an approximate method and sometimes does not have the capability to incorporate every detail of the problem, namely a specific probability density function or more specific limit conditions.