压电智能结构模糊自学习控制(FSLC)

将模糊逻辑与学习控制的基本思想相结合,根据控制系统的动态输出特性,采用模糊控制对学习控制律中的参数进行实时校正,实现系统的动态学习过程,提出了一种适用于压电智能结构振动控制的模糊自学控制方法FSLC（FuzzySelf-LearningContr01）。分别采用三维8节点实体单元（Solid45）和耦合单元模拟主结构和压电致动器／传感器,基于ANSYS参数化语言编写了压电智能结构振动控制分析的有限元程序。通过数值仿真证明了模糊自学习控制方法能有效控制压电结构的振动,并提高了自学习控制的收敛速度和获得了很好的控制效果。     

柔性空间机械臂协调运动的鲁棒神经网络控制及柔性振动PD反馈控制

针对具有未知惯性参数柔性空间机械臂系统的动力学和柔性振动控制问题,设计了基于奇异摄动理论的载体、关节铰轨迹跟踪的鲁棒神经网络控制算法和柔性振动反馈PD控制算法.首先,构建神经网络函数逼近慢变子系统的综合建模误差,设计载体、关节铰协调运动鲁棒控制算法,同时,通过稳定性分析选择神经网络自适应律;应用PD反馈控制来主动控制并消除快变子系统的柔性振动模态.仿真结果表明,所设计的控制算法解决了系统参数未知等因素带来的影响,能快速准确地进行轨迹追踪,同时,柔性杆的振动模态得到明显抑制,在2秒后基本消除.     

基于神经网络算法的建筑结构振动分散控制研究

针对地震作用下建筑结构振动分散控制问题,引入神经网络算法,研究结构振动分散神经网络控制策略,来解决分散控制中各子系统的耦合问题和神经网络算法的训练成本问题.利用径向基函数RBF(Radical Basis Function)神经网络模型并基于newrb函数构建了RBF神经网络控制器,对某20层Benchmark结构模型分别进行集中控制和多工况子系统划分分散控制的数值模拟分析,结果表明,提出的各子系统耦合的分散RBF神经网络振动控制策略考虑了子系统间的信息共享,可有效控制结构的振动响应,且子系统达到理想训练结果所需的训练次数与BP网络相比显著降低.     

结构基于独立模态空间控制的神经网络控制

在对柔性结构振动的主动控制中，独立模态空间控制是一种适合于柔性结构振动控制的方法，但如果控制器选择不好就会带来观测溢出和控制溢出．神经网络控制则具有较好的泛化作用和鲁棒性，对抑制观测溢出和控制溢出具有较好的效果．本在独立模态空间控制的基础上设计了一种神经网络控制，并对柔性梁及板进行了控制的数值仿真，取得了较好的效果．     

涡激响应尾流双振子模型的参数反演方法

尾流双振子模型是研究圆柱结构涡激振动响应的重要模型,模型参数的准确确定对悬浮隧道设计理论具有重要意义.首先通过降阶法将多变量二阶非线性常微分方程组的尾流双振子模型变换为一阶方程组.然后给出一种新型的圆柱结构水槽试验设计方案,其中试验模型的刚度能够较好反映悬浮隧道等实际工程结构的刚度,基于相机动态捕捉和视频识别计算机程序,获取圆柱结构在水平和竖直方向的位移试验数据.基于试验结果和龙格-库塔方法求解一阶方程组,采用BP神经网络智能算法对模型参数进行反演,同时利用遗传算法对神经元的初始权值和阈值进行优化,所得结果平均误差仅为5.50％,优于遗传算法和未优化的BP神经网络模型.结果表明,基于遗传算法优化的BP神经网络智能算法能够精确实现尾流双振子模型的参数确定,为圆柱结构涡激振动响应分析提供理论基础.     

地震作用下高层建筑结构的分散神经网络振动控制研究

针对地震作用下高层建筑振动神经网络控制问题,将神经网络理论与分散控制理论相结合,提出分散神经网络振动控制方案,并应用于高层结构地震反应振动控制中。利用多层前馈神经网络建立结构模型,预测结构的振动响应。基于NARMA-L2的神经自校正控制系统设计BP神经网络控制器,研究分散神经网络振动控制效果,并与神经网络集中控制进行比较。对某20层Benchmark结构模型进行数值模拟分析,结果表明,本文提出的分散神经网络振动控制方法简化了神经网络的结构,可有效控制结构振动和消除时滞;同时,相对于集中控制的单一失效,本文方法的可靠性更强且可以保证振动控制系统的实时响应。     

基于自适应神经元的结构振动智能PID控制

首先提出基于自适应神经元的振动智能ＰＩＤ控制策略及相应高效算法，然后通过数字仿真与模型实验验证了这种算法的有效性。这种方法具有控制器参数少、结构简单、算法收敛速度快、便于实时控制等优点。与传统ＰＩＤ控制相比，控制器参数整定可通过神经网络的自组织来实现。数字仿真与实验结果表明这种方法能够有效地控制动态特性未知、所受干扰不可测的黑箱振动系统的任意振动     

模型不确定压电柔性结构的多目标振动控制

以压电柔性结构为对象,考虑其被控模态参数的不确定性和因剔除残余模态所引起的动态不确定性,建立了结构的不确定线性分式模型;根据不确定模型设计了一个对结构进行振动控制的动态输出反馈控制器,使闭环系统满足鲁棒稳定、扰动抑制、极点配置约束及控制输入约束等性能要求;并利用线性矩阵不等式,将具有多个性能要求的振动控制问题转化为具有线性矩阵不等式约束和线性目标函数的凸优化问题。最后以简支压电柔性梁为例,设计了一个融合多性能指标的动态输出反馈非同位控制器,并给出了仿真结果。     

模糊—神经网络控制算法及其在离心力—振动复合环境试验系统中的应用

针对离心－振动复合环境试验系统所存在的耦合性、非线性和不确定性提出了一种模糊－神经网络控制算法,利用被控对象输入输出信息离线、在线相结合学习系统的动态特性,对时变、非线性系统进行跟踪控制,并研究了该算法在系统中的实现方法。实现表明了控制系统具有良好的跟踪能力。该算法也适用于快速变化这类系统的实时控制。     

基于极大似然估计的BP算法及其在深基坑开挖参数辨识中的应用

本文采用人工神经网络BP算法对深基坑开挖工程中的参数进行辨识,将某些现场实测值作为网络输入,土层物性参数作为网络的输出, 限元计算取得学习样本来训练网络,从而地深基坑开挖工程中的参数进行辨识的目的,同时,本文提出了将极大似然估计引入BP学习算法中,可以考虑学习样本和网络输入（现场产测值）的误差,可以求得所辨识参数的可靠度,本文还对动态调整BP学习算法的学习速度因子,冲量系数以加快网络学习速度的算法进行了研究,本文算例表明本文算法训练速率可比传统BP算法快10倍以上。     

High performance fuzzy-Padé controllers: Introduction and comparison to fuzzy controllers

In this paper, a new highly convergent, efficient, and fast response control technique entitled as fuzzy-Padé control method is introduced. It provides a simple methodology to exploit the heuristic knowledge in controlling a system. Fuzzy–Padé controllers originate from a unification of heuristic knowledge expressed as the rule base, and Padé approximants. In this method, fuzzy singleton rules are used to generate the rule base. Accordingly, unknown parameters in the Padé approximant are determined using these rules. The fuzzy-Padé controllers possess certain advantages over fuzzy controllers, and they can be applied in situations where fuzzy controllers previously failed. To demonstrate the effectiveness and robustness of the method, the simulation results for three case studies, the single inverted pendulum, ball and beam, and parallel double inverted pendulum systems are presented. In the case studies, it is shown that the fuzzy-Padé controller has greater convergence region, is quite faster, and its energy consumption is much lower than the fuzzy controller.     

A control approach for vibrations of a nonlinear microbeam system in multi-dimensional form

Microbeams are widely seen in micro-electro-mechanical systems and their engineering applications. An active control strategy based on the fuzzy sliding mode control is developed in this research for controlling and stabilizing the nonlinear vibrations of a micro-electro-mechanical beam. An Euler-Bernoulli beam with a fixed-fixed boundary is employed to represent the microbeam, and the geometric nonlinearity of the beam and loading nonlinearity from the electrostatic force are considered. The governing equation of the microbeam is established and transformed into a multi-dimensional dynamic system with the third-order Galerkin method. A stability analysis is provided to show the necessity of the derived multi-dimensional dynamic system, and a chaotic motion is discovered. Then, a control approach is proposed, including a control strategy and a two-phase control method. For describing the application of the control approach developed, control of a chaotic motion of the microbeam is presented. The effectiveness of the active control approach is demonstrated via controlling and stabilizing the nonlinear vibration of the microbeam.     

Design and Implementation of a Pointer System Controller

The development of a pointer system as used for space structures, is discussed. The pointer has to keep its signal on a stationary target. The pointer itself is mounted on a supporting system which is excited in a plane either parallel or normal to the pointer-target beam. A fuzzy logic control system has been adopted due to the geometric nonlinearities of the problem.     

压电激励圆形曲梁的静态响应及位移控制

研究压电激励圆形曲梁的静态位移响应及位移控制的参数特性。将压电夹层圆形曲梁等效为单层结构,基于一维小曲率曲梁理论,建立其控制方程。在集中弯矩和径向集中力以及电载荷作用下,分析了带压电激励器的圆形悬臂曲梁的静态响应。与有限元结果比较表明:本文的理论模型能够模拟压电激励的小曲率圆形曲梁的静态响应。压电夹层圆形曲梁在任意位置的径向集中力载荷作用下,控制其自由端径向位移响应为零,求得控制电压的解析表达,数值分析表明:随着集中力载荷的位置变化和梁长的变化,最优控制电压将出现峰值和反号。     

Observer-based adaptive fuzzy backstepping control of MIMO stochastic nonlinear strict-feedback systems

In this paper, an adaptive fuzzy output feedback control approach is proposed for a class of multiinput and multioutput (MIMO) uncertain stochastic nonlinear strict-feedback systems without the measurements of the states. The fuzzy logic systems are used to approximate the unknown nonlinear functions, and a fuzzy state observer is designed for estimating the unmeasured states. Utilizing the designed the fuzzy state observer and by combining the adaptive backstepping control design, an adaptive fuzzy output feedback control approach is developed. It is proved that the proposed control approach can guarantee that all the signals of the closed-loop system are semiglobally uniformly ultimately bounded (SUUB) in probability, and the observer errors and the output of the system converge to a small neighborhood of the origin by appropriate choice of the design parameters. A simulation example is provided to show the effectiveness of the proposed approach.     

Fuzzy variational principle and its applications

Linear and non-linear peaky fuzzy numbers and their arithmetic operations are constructed for the analysis of engineering structures with fuzzy characteristic quantities. Fuzziness of the corresponding quantities is consistently incorporated into the functional of the total potential energy. A set of deterministic recursive equations is obtained as the alternative expressions of the fuzzy variational principle by means of the second-order perturbation technique. The fuzzy Ritz method and the fuzzy finite element method are presented as the applications of the fuzzy variational principle. Accordingly, the roundabout procedures frequently used in the formulations of the fuzzy finite element method are avoided. A benchmark problem of a bending beam with fuzzy Young's modulus under fuzzy external loading is solved by the developed fuzzy numerical methods. Numerical examples show that results determined by these two fuzzy methods are both little conservative, and are in good agreement with those obtained by the analytical method. Moreover, the fuzzy Ritz method or the fuzzy finite element method can provide more valuable information than the conventional deterministic methods.     

Adaptive interval type-2 fuzzy sliding mode control for unknown chaotic system

In this paper, a novel adaptive interval type-2 fuzzy sliding mode control (AIT2FSMC) methodology is proposed based on the integration of sliding mode control and adaptive interval type-2 fuzzy control for chaotic system. The AIT2FSMC system is comprised of a fuzzy control design and a hitting control design. In the fuzzy control design, an interval type-2 fuzzy controller is designed to mimic a feedback linearization (FL) control law. In the hitting control design, a hitting controller is designed to compensate the approximation error between the FL control law and the interval type-2 fuzzy controller. The parameters of the interval type-2 fuzzy controller, as well as the uncertainty bound of the approximation error, are tuned adaptively. The adaptive laws are derived in the sense of Lyapunov stability theorem, thus the stability of the system can be guaranteed. The proposed control system compared to adaptive fuzzy sliding mode control (AFSMC). Simulation results show that the proposed control systems can achieve favorable performance and robust with respect to system uncertainties and external disturbances.     

Discrete adaptive fuzzy control for asymptotic tracking of robotic manipulators

This paper presents a novel discrete adaptive fuzzy controller for electrically driven robot manipulators. It addresses how to overcome the nonlinearity, uncertainties, discretizing error and approximation error of the fuzzy system for asymptotic tracking control of robotic manipulators. The proposed controller is model-free in the form of discrete Mamdani fuzzy controller. The parameters of fuzzy controller are adaptively tuned using an adaptive mechanism derived by stability analysis. A robust control term is used to compensate the approximation error of the fuzzy system for asymptotic tracking of a desired trajectory. The controller is robust against all uncertainties associated with the robot manipulator and actuators. It is easy to implement since it requires only the joint position feedback. Compared with fuzzy controllers which employ all states to guarantee stability, the proposed controller is very simpler. Stability analysis and simulation results show its efficiency in the tracking control.     

DYNAMIC CHARACTERISTIC ANALYSIS OF FUZZY- STOCHASTIC TRUSS STRUCTURES BASED ON FUZZY FACTOR METHOD AND RANDOM FACTOR METHOD

A new fuzzy stochastic finite element method based on the fuzzy factor method and random factor method is given and the analysis of structural dynamic characteristic for fuzzy stochastic truss structures is presented. Considering the fuzzy randomness of the structural physical parameters and geometric dimensions simultaneously, the structural stiffness and mass matrices are constructed based on the fuzzy factor method and random factor method; from the Rayleigh's quotient of structural vibration, the structural fuzzy random dynamic characteristic is obtained by means of the interval arithmetic; the fuzzy numeric characteristics of dynamic characteristic are then derived by using the random variable's moment function method and algebra synthesis method. Two examples are used to illustrate the validity and rationality of the method given. The advantage of this method is that the effect of the fuzzy randomness of one of the structural parameters on the fuzzy randomness of the dynamic characteristic can be reflected expediently and objectively.