基于可能性理论的结构模糊可靠性方法

利用模糊变量描述结构的不确定性 ,基于可能性理论和模糊区间分析 ,依据基于区间分析的非概率可靠性方法 ,建立了用于模糊结构和系统的能度可靠性模型。该模型可给出模糊可靠性指标的可能性分布和结构失效的可能性度量 ,并提供更多的关于结构安全程度的有用信息 ,且应用简便。算例分析说明了文中方法的应用     

细长结构几何非线性分析的子结构方法

将细长结构沿长度方向划分为多个子结构,并在每个子结构上建立一个随结构一起运动的连体基,则结构内任意点的位移可分解为连体基的转动和相对于连体基的小位移。利用细长结构这样的变形特征,本文详细讨论了连体基的转动,给出了与连体基选择方式相协调的节点位移及其虚变分表达式,并将子结构内部位移凝聚到了边界节点上。在此基础上,提出了一种细长结构几何非线性分析的子结构方法,可在不损失计算精度的前提下大幅度降低求解规模,从而提高了计算效率。数值算例验证了所提方法的有效性。     

PROCEDURE FOR COMPUTING THE POSSIBILITY AND FUZZY PROBABILITY OF FAILURE OF STRUCTURES

ＩｎｔｒｏｄｕｃｔｉｏｎＴｈｅｉｎｉｔｉａｔｉｏｎｏｆｒｅｌｉａｂｉｌｉｔｙｔｅｃｈｎｉｑｕｅｓｗａｓｄｕｅｔｏｔｈｅｅｘｉｓｔｅｎｃｅｏｆｌａｒｇｅａｍｏｕｎｔｏｆｕｎｃｅｒｔａｉｎｔｉｅｓｉｎｅｎｇｉｎｅｅｒｉｎｇ .Ａｃｃｏｒｄｉｎｇｔｏｔｈｅｄｉｆｆｅｒｅｎｃｅｓｉｎｔｈｅｐｒｏｄｕｃｅｄｃａｕｓｅａｎｄｐｈｙｓｉｃａｌｍｅａｎｉｎｇ,ｕｎｃｅｒｔａｉｎｔｉｅｓｍａｙｂｅｄｉｖｉｄｅｄｇｅｎｅｒａｌｌｙｉｎｔｏｔｈｒｅｅｔｙｐｅｓ:ｒａｎｄｏｍｎｅｓｓ,ｆｕｚｚｉｎｅｓｓａｎｄｕｎａｓｃｅｒ…     

Theory and solution of general fuzzy optimization for structures

In order to consider the overall fuzzy factors and fuzzy information in optimum design of engineering structures, the theory and solution of general fuzzy programming with wide generality are proposed in this paper. On the basis of this programming, an example of structural optimum design with multi-objective is given.     

Geometric and material nonlinear analysis of tensegrity structures

A numerical method is presented for the large deflection in elastic analysis of tensegrity structures including both geometric and material nonlinearities.The geometric nonlinearity is considered based on both total Lagrangian and updated Lagrangian formulations,while the material nonlinearity is treated through elastoplastic stress-strain relationship.The nonlinear equilibrium equations are solved using an incremental-iterative scheme in conjunction with the modified Newton-Raphson method.A computer program is developed to predict the mechanical responses of tensegrity systems under tensile,compressive and flexural loadings.Numerical results obtained are compared with those reported in the literature to demonstrate the accuracy and efficiency of the proposed program.The flexural behavior of the double layer quadruplex tensegrity grid is sufficiently good for lightweight large-span structural applications.On the other hand,its bending strength capacity is not sensitive to the self-stress level.     

Self-tuning fuzzy logic control of a non-linear structural system with ATMD against earthquake

Self-tuning fuzzy logic controllers (STFLC) for the active control of Marmara Kocaeli earthquake excited building structures are studied in this paper. Vibration control using intelligent controllers, such as fuzzy logic has attracted the attention of structural control engineers during the last few years, because fuzzy logic can handle nonlinearities, uncertainties, and heuristic knowledge effectively and easily. The improved seismic control performance can be achieved by converting a simply designed static gain into a real time variable dynamic gain through a self-tuning mechanism. Self-tuning fuzzy logic controller is designed to reduce the story-drift of each floor. The simulated system has a nine-degree-of-freedom, which is modeled using nonlinear behavior of the base-structure interaction. Modeled system was simulated against the ground motion of the Marmara Kocaeli earthquake (M _w=7.4) in Turkey on 17 August, 1999. At the end of the study, the time history of the story displacements, accelerations, ATMD displacements, control voltage, and frequency responses of the both uncontrolled and controlled cases are presented. The robustness of the controller has been checked through the uncertainty in stiffness of the structure. Performance of the designed STFLC has been demonstrated for the different disturbance using ground motion of the Kobe earthquake. Simulations of an earthquake excited nine story structure are performed to prove the validity of proposed control strategy.     

基于模糊事件概率理论的模糊可靠性分析通用方法

讨论了从已知的模糊信息的隶属函数,确定模糊失效事件的隶属函数的方法,以便能利用模糊事件概率理论进行模糊可靠性分析,给出模糊可靠性分析通用而统一的方法;并给出了强度为几种常用模糊分布时,所确定的模糊失效事件的隶属函数的具体表达式,分析了模糊失效事件的隶属函数的曲线特性。由于获得的模糊失效事件的隶属函数的形式比较复杂,用模糊事件概率理论进行模糊可靠性分析时,不可能得到计算模糊失效事件概率的解析式,因此通过仿真所确定的模糊失效事件的隶属函数的数学期望的方法,估计模糊失效事件的发生概率。本文讨论的通过确定模糊事件的隶属函数,用模糊事件概率理论进行模糊可靠性分析的方法具有普遍意义。     

基于模糊逻辑控制的舰船组合导航自适应卡尔曼滤波器

双天线GPS提供的载体姿态信息与惯性导航系统信息进行融合可提高组合导航系统的性能。由于在实际应用中,GPS接收机可能会受到某种干扰无法提供舰船航向信息,从而降低传统卡尔曼滤波器的性能。因而提出了一种新的基于模糊逻辑控制的自适应卡尔曼滤波器。改进后的卡尔曼滤波器使用两个模糊逻辑控制器来调整两个系统的组合模式,并且根据卡尔曼滤波器的内部状态、GPS工作状态和舰船运动状态来计算卡尔曼增益。通过使用INS和GPS的实测数据验证,这种基于模糊逻辑控制的自适应卡尔曼滤波器能有效的提高INS/GPS组合导航系统的性能。     

基于磁流变阻尼器的多单体组合隔震结构模糊控制研究

提出了一种新的组合结构振动控制体系——多单体组合隔震结构,建立了力学模型及运动方程。基于瞬时最优控制算法,将控制力表达成阻尼力的形式,用磁流变阻尼器充当控制器,运用模糊控制方法对其进行控制。通过计算机仿真分析,并运用LQR控制与之进行对比。研究结果表明,这种组合隔震结构体系的控制效果明显,各结构的地震响应都有明显降低。采用模糊控制不需要建立精确的计算模型,并能达到与LQR控制相接近的控制效果。用磁流变阻尼器充当控制器减少了能量输入,在结构2与结构3之间安装弹簧-阻尼器使控制更容易实现。     

基于模糊神经网络的结构非模型主动控制

本文将模糊人工神经网络运用到结构的主动控制中，用模糊联想记忆（ＦＡＭ）神经网络作为控制器，对在地震力下的结构振动进行主动控制，控制过程中无须引入结构的运动模型和精确参数。数值仿真的结果表明，该控制系统具有适应能力强，消振迅速且效果良好的特点。     

利用结构基因法研究非线性周期性板结构的等效力学性能

非线性周期性板结构是一类在智能复合材料领域具有巨大应用潜力的结构,因其构成材料的非线性特性,以及结构中经常包含增强纤维、肋板和空洞等复杂微结构导致的材料几何非线性,利用常规的有限元方法进行建模和分析较为困难.本文提出了一种结构基因法,通过提取非线性周期性板结构的最小模型单元作为其结构基因,将异质周期性板结构等效为均质板结构,便捷地求解了非线性周期性板结构的微观力学性能和整体等效力学性能.算例表明,结构基因方法可用来分析复杂非线性复合材料结构问题,计算结果精度足够,为复合材料微观力学研究提供了有价值的参考.     

Multiobjective fuzzy optimum design of antenna structures

On the basis of the recently proposed general fuzzy optimization [1–2], this paper investigates the multiobjective fuzzy optimum design of antenna structures, in which the weight objective, precision objective, lowest frequency objective and safety degree objective are included. This is a successful application of fuzzy optimization to large engineering structures.     

直接基于单元平衡的梁非线性分析方法

以单元力平衡条件为基础建立的梁单元在近年来受到广泛关注,与传统的以单元位移相容条件为基础建立的梁单元相比,基于平衡的梁单元可获得较高的精度。针对基于平衡的梁单元,给出了一种几何非线性分析方法,使用该方法进行几何非线性分析时不需进行单元内部位移场的构造,避免了使用现有位移场构造方法时可能引起的振荡问题,同时降低了有限元程...     

Modeling and control of a nonlinear half-vehicle suspension system: a hybrid fuzzy logic approach

Modeling and control of vehicle suspension system are high noteworthy from safety to comfort. In this paper, an analytical nonlinear half-vehicle model which is included quadratic tire stiffness, cubic suspension stiffness, and coulomb friction is derived based on fundamental physics. A hybrid fuzzy logic approach which combines fuzzy logic and PID controllers is designed for reducing the vibration levels of passenger seat and vehicle body. Performances of designed controllers have been evaluated by numerical simulations. Comparisons with classical PID control, Fuzzy Logic Control (FLC) and Hybrid Fuzzy-PID control (HFPID) have also been provided. Results of numerical simulations are evaluated in terms of time histories of displacement and acceleration responses and ride index comparison. A good performance for the Hybrid Fuzzy-PID controller with coupled rules (HFPIDCR) is achieved in simulation studies despite the nonlinearities.     

A differential flatness theory approach to observer-based adaptive fuzzy control of MIMO nonlinear dynamical systems

The paper proposes a solution to the problem of observer-based adaptive fuzzy control for MIMO nonlinear dynamical systems (e.g. robotic manipulators). An adaptive fuzzy controller is designed for a class of nonlinear systems, under the constraint that only the system’s output is measured and that the system’s model is unknown. The control algorithm aims at satisfying the $H_\infty $ tracking performance criterion, which means that the influence of the modeling errors and the external disturbances on the tracking error is attenuated to an arbitrary desirable level. After transforming the MIMO system into the canonical form, the resulting control inputs are shown to contain nonlinear elements which depend on the system’s parameters. The nonlinear terms which appear in the control inputs are approximated with the use of neuro-fuzzy networks. Moreover, since only the system’s output is measurable the complete state vector has to be reconstructed with the use of a state observer. It is shown that a suitable learning law can be defined for the aforementioned neuro-fuzzy approximators so as to preserve the closed-loop system stability. With the use of Lyapunov stability analysis, it is proven that the proposed observer-based adaptive fuzzy control scheme results in $H_{\infty }$ tracking performance.     

基于模糊逻辑的光纤陀螺温度补偿技术

为了消除温度效应并提高陀螺精度,将模糊逻辑应用于光纤陀螺的温度漂移模型的辨识和自补偿中方案中。在模糊逻辑理论的框架下,根据光纤陀螺系统的模糊信息,建立模糊规则,进行模糊推理,实现对陀螺输出的近似辨识。此方法对其他没有温度相似性的陀螺也适用。在实际验证实验中,针对不同的陀螺,通过预先实验建立各自的规则表,然后进行实时补偿,在全温度范围内陀螺的零偏稳定性从0.3647(o)/h减小到0.0868(o)/h,陀螺预热时间缩短到30s以内。目前,在陀螺工艺条件还不够稳定的状态下,此方案是实用和可行的。     

Adaptive Feedback Linearization for the Control of a Typical Wing Section with Structural Nonlinearity

Earlier results by the authors showed constructions of Lie algebraic, partial feedback linearizing control methods for pitch and plunge primary control utilizing a single trailing edge actuator. In addition, a globally stable nonlinear adaptive control method was derived for a structurally nonlinear wing section with both a leading and trailing edge actuator. However, the global stability result described in a previous paper by the authors, while highly desirable, relied on the fact that the leading and trailing edge actuators rendered the system exactly feedback linearizable via Lie algebraic methods. In this paper, the authors derive an adaptive, nonlinear feedback control methodology for a structurally nonlinear typical wing section. The technique is advantageous in that the adaptive control is derived utilizing an explicit parameterization of the structural nonlinearity and a partial feedback linearizing control that is parametrically dependent is defined via Lie algebraic methods. The closed loop stability of the system is guaranteed to be stable via application of La Salle's invariance principle.     

Distributed adaptive fuzzy control approach for prescribed-time containment of uncertain nonlinear multi-agent systems with unknown hysteresis

Nonlinear Dynamics - Unknown hysteresis cannot be ignored in containment control, but the problem of prescribed-time containment for uncertain nonlinear multi-agent systems with unknown hysteresis...     

Fuzzy reliability analysis of aseismic structures

The structural reliability analysis taking account of the fuzziness in both earthquake loads and structural resistances is put forward in this paper. For this purpose, the concepts such as fuzzy earthquake intensity, fuzzy response spectrum, fuzzy structural response and satisfaction degree to fuzzy-random constraint are defined. This procedure may be taken as a basis for establishing a more rational optimum design of structures.