Convergence analysis of first order reliability method using chaos theory

First order reliability method (FORM) for the computation of reliability index has been used widely because of its advantages of the efficiency and effectiveness as well simplicity for many years. There exists the phenomenon of convergent failure in the FORM in calculating the reliability index iteratively for some limit state functions, for which the essential factor is investigated using chaotic dynamics theory in the present paper. The bifurcation plots of reliability index are presented for several typical limit state functions, and the computational results from those mapping functions due to FORM iterations show the complicated dynamics phenomena such as the periodic oscillation, bifurcation and chaos. Moreover, the Lyapunov exponents of non-linear map from FORM are calculated. From the numerical investigation of presented examples, it is concluded that the convergence of FORM does not depend on the curvature of design points of the limit state function, and the quantitative index for identifying the convergence of FORM iterative computation is the Lyapunov exponents of non-linear map corresponding to that limit state function.     

Chaos control of performance measure approach for evaluation of probabilistic constraints

Performance measure approach (PMA) is a recently proposed method for evaluation of probabilistic constraints in reliability-based design optimization of structure. The advanced mean-value (AMV) method is well suitable for PMA due to its simplicity and efficiency. However, when the AMV iterative scheme is applied to search for the minimum performance target point for some nonlinear performance functions, the iterative sequences could fall into the periodic oscillation and even chaos. In the present paper, the phenomena of numerical instabilities of AMV iterative solutions are illustrated firstly. And the chaotic dynamics analysis on the iterative procedure of AMV method is performed. Then, the stability transformation method of chaos feedback control is suggested for the convergence control of AMV procedure in the parameter interval in which the iterative scheme fails. Numerical results of several nonlinear performance functions demonstrate that the control of periodic oscillation, bifurcation and chaos for AMV iterative procedure is achieved, and the stable convergence solutions are obtained.     

A robust iterative algorithm for structural reliability analysis

In the “first-order reliability method” (FORM), the HL-RF iterative algorithm is a recommended and widely used one to locate the design point and calculate the reliability index. However it may fail to converge if the limit state surface at the design point is highly nonlinear. In this paper, an easy iterative algorithm, which introduces a “new” step length to control the convergence of the sequence and can be named as finite-step-length iterative algorithm, is present. It is proved that the HL-RF method is a special case of this proposed algorithm when the step length tends to infinity and the reason why the HL-RF diverges is illustrated. This proposed algorithm is much easier than other optimization schemes, especially than the modified HL-RF algorithm, because the process of line search for obtaining the step length is not needed. Numerical results indicate that the proposed algorithm is effective and as simple as the HL-RF but more robust.     

Logistic阻滞增长模型的计算机模拟

将Logistic阻滞增长模型的差分形式进行简化,对Logistic模型的简化差分形式进行迭代求解,做出了随固有增长率r的变化,序列狖yk狚收敛、2倍周期、4倍周期……直至一片混乱的图形。以参数b为横坐标、序列狖yk狚的收敛点为纵坐标,用MATLAB数学软件模拟展示了这一简单差分方程从收敛、分叉、2n倍周期收敛进入混沌现象的过程。     

Convergence control of single loop approach for reliability-based design optimization

For solution of reliability-based design optimization (RBDO) problems, single loop approach (SLA) shows high efficiency. Thus SLA is extensively used in RBDO. However, the iteration solution procedure by SLA is often oscillatory and non-convergent for RBDO with nonlinear performance function. This prevents the application of SLA to engineering design problems. In this paper, the chaotic single loop approach (CLSA) is proposed to achieve the convergence control of original iterative algorithm in SLA. The modification involves automated selection of the chaos control factor by solving a novel one-dimensional optimization model. Additionally, a new oscillation-checking method is constructed to detect the oscillation of iterative process of design variables. The computational capability of CLSA is demonstrated through five benchmark examples and one stiffened shell application. The comparison of numerical results indicates that CSLA is more efficient than the double loop approach and the decoupled approach. CSLA also solves the RBDO problems with highly nonlinear performance function and non-normal random variables stably.     

求解旅行商问题的混合粒子群优化算法

为高效解决旅行商问题,结合光学寻优算法、混沌优化算法、粒子群优化算法,提出了一种新的混合智能优化算法,应用光学寻优算法的优点,为粒子群中粒子找到了一组最优的初始值,引入交换子、交换序列、混沌序列,提出了适合旅行商问题的光学混沌粒子群算——并严格证明了新算法的稳定性、收敛性.数值实验仿真结果表明,该算法收敛速度快、迭代次数少,能快速找到令人满意的最优解,为解决旅行商问题提供了新的思路.     

Reliability sensitivity analysis for structural systems in interval probability form

Reliability sensitivity analysis is used to find the rate of change in the probability of failure (or reliability) due to the changes in distribution parameters such as the means and standard deviations. Most of the existing reliability sensitivity analysis methods assume that all the probabilities and distribution parameters are precisely known. That is, every statistical parameter involved is perfectly determined. However, there are two types of uncertainties, epistemic and aleatory uncertainties that may not be perfectly determined in engineering practices. In this paper, both epistemic and aleatory uncertainties are considered in reliability sensitivity analysis and modeled using P-boxes. The proposed method is based on Monte Carlo simulation (MCS), weighted regression, interval algorithm and first order reliability method (FORM). We linearize original non-linear limit-state function by MCS rather than by expansion as a first order Taylor series at most probable point (MPP) because the MPP search is an iterative optimization process. Finally, we introduce an optimization model for sensitivity analysis under both aleatory and epistemic uncertainties. Four numerical examples are presented to demonstrate the proposed method.     

轮式机器人轨迹跟踪控制系统的设计

针对轮式机器人轨迹跟踪控制系统误差收敛速率低、精度和实时性差的问题,采用反演控制算法并结合李雅普诺夫稳定性分析方法对轮式机器人的轨迹跟踪系统进行了优化设计;建立了轮式机器人轨迹跟踪控制系统的运动学模型,并对该模型进行位置偏差分析;在反演控制算法中引入了分部虚拟控制量,并分析和设计了其他间接受控量,提高了算法运行的效率;采用李雅普诺夫收敛定理对系统的收敛性进行分析,根据分析的结果提出了算法更加简单的控制律;利用Matlab软件的Simulink库对设计的轨迹跟踪控制系统试验研究;结果表明,与基于李雅普诺夫直接法或者迭代学习算法设计的轮式机器人轨迹跟踪控制系统相比较,设计的控制系统具有跟踪精度高、收敛速度快、实时性好的优点。     

Controlling Chaos and Neimark–Sacker Bifurcation in a Host–Parasitoid Model

In this paper, a new density‐dependent host–parasitoid model is proposed. The modification is based on density‐dependent factor by introducing Hassell growth function in host population. Moreover, the permanence of solutions, existence and uniqueness of positive equilibrium, local asymptotic stability and global behavior of the positive equilibrium point are also investigated. It is demonstrated that system endures Neimark–Sacker bifurcation for wide range of bifurcation parameter. In order to control chaos due to emergence of Neimark–Sacker bifurcation, two feedback control strategies, that is, OGY and hybrid control methods are implemented. Finally, all mathematical analysis, particularly, Neimark–Sacker bifurcation, chaos control strategies, and global asymptotic stability of unique positive point are verified with the help of numerical simulations.     

用状态变量的一阶微分反馈法实现蔡电路的混沌控制

提出了用系统变量的一阶微分反馈实现Chua电路的分岔和混沌控制的方法.首先根据理论分析,求出使混沌Chua电路中不动点稳定时控制参数k1的取值范围和使系统发生Hopf分岔时控制参数k₁的临界值k₀.由分岔图可以得到系统被控制到各种nP周期轨道时k₁的取值范围.然后根据该控制方法,设计了实现Chua电路混沌控制的电路,并进行了电路仿真.数值计算和仿真结果验证了这种控制分岔和混沌方法的正确性和有效性.     

基于Hénon映射的自适应克隆选择优化算法

免疫算法与遗传算法都存在的不成熟收敛问题。混沌优化方法是近年出现一种新的优化技术,通常使用Logistic或Tent映射产生混沌序列进行搜索,Logistic映射产生的混沌序列的概率密度函数切比雪夫型分布,当最优值落在[0,1]的中间位置时,这种分布特性会影响全局搜索能力和效率。而Tent映射也存在迭代易落入小周期循环的问题。针对免疫算法和混沌优化算法中存在的缺陷,该文用变尺度的搜索策略,提出了一种基于Hénon映射的自适应克隆选择的优化算法,数值仿真结果表明,该文提出的算法提高了局部搜索的能力及其计算效率,算法可行有效。     

A new adaptive mutative scale chaos optimization algorithm and its application

Based on results of chaos characteristics comparing one-dimensional iterative chaotic self-map x = sin（2/x） with infinite collapses within the finite region[-1, 1] to some representative iterative chaotic maps with finite collapses （e.g., Logistic map, Tent map, and Chebyshev map）, a new adaptive mutative scale chaos optimization algorithm （AMSCOA） is proposed by using the chaos model x = sin（2/x）. In the optimization algorithm, in order to ensure its advantage of speed convergence and high precision in the seeking optimization process, some measures are taken： 1） the searching space of optimized variables is reduced continuously due to adaptive mutative scale method and the searching precision is enhanced accordingly; 2） the most circle time is regarded as its control guideline. The calculation examples about three testing functions reveal that the adaptive mutative scale chaos optimization algorithm has both high searching speed and precision.     

自治分段线性振荡系统的离散映射数值建模与稳定性分析

为研究自治分段线性振荡系统中出现的分叉及混沌动力学行为,系统建模及稳定性分析是一种必不可少的分析手段. 本文通过构造周期内离散映射解析模型,并结合边界条件的动态数值求解,提出了一种动态离散映射数值建模方法,进而推导了用以判定系统周期闭轨稳定性的Jacobian 矩阵求解模型. 最后,本文以电力电子系统中一种常用的5 维软开关逆变自治振荡电路作为实例,通过模型仿真观察到频率的分叉现象,并根据Jacobian 矩阵的特征乘数对系统的稳定性进行了研究. 基于该模型的仿真分析结果与实验系统中所观察到的现象一致,从而验证了该方法的有效性.     

融合递减策略与Fuch混沌机制的改进YSGA算法

为增强绯鲵鲣算法搜索的覆盖性及寻优的精准性以优化全局探索能力和局部开采能力,提出一种融合步长因子递减策略与混沌局部增强机制的改进绯鲵鲣优化算法(IYSGA).首先,该改进算法在标准YSGA算法基础上,设计了一种动态的步长因子递变模式以实现绯鲵鲣算法高效全面的搜索,此策略有利于提高算法的搜索效率并扩大寻优范围;其次,混沌...     

A relaxation method of an alternating iterative algorithm for the Cauchy problem in linear isotropic elasticity

We propose two algorithms involving the relaxation of either the given Dirichlet data (boundary displacements) or the prescribed Neumann data (boundary tractions) on the over-specified boundary in the case of the alternating iterative algorithm of Kozlov et al. [16] applied to Cauchy problems in linear elasticity. A convergence proof of these relaxation methods is given, along with a stopping criterion. The numerical results obtained using these procedures, in conjunction with the boundary element method (BEM), show the numerical stability, convergence, consistency and computational efficiency of the proposed method.     

A design method for indirect iterative learning control based on two-dimensional generalized predictive control algorithm

Indirect iterative learning control (ILC) facilitates the application of learning-type control strategies to the repetitive/batch/periodic processes with local feedback control already. Based on the two-dimensional generalized predictive control (2D-GPC) algorithm, a new design method is proposed in this paper for an indirect ILC system which consists of a model predictive control (MPC) in the inner loop and a simple ILC in the outer loop. The major advantage of the proposed design method is realizing an integrated optimization for the parameters of existing feedback controller and design of a simple iterative learning controller, and then ensuring the optimal control performance of the whole system in sense of 2D-GPC. From the analysis of the control law, it is found that the proposed indirect ILC law can be directly obtained from a standard GPC law and the stability and convergence of the closed-loop control system can be analyzed by a simple criterion. It is an applicable and effective solution for the application of ILC scheme to the industry processes, which can be seen clearly from the numerical simulations as well as the comparisons with the other solutions.     

Host-Parasitoid系统的分岔与混沌控制

用数值模拟的方法,研究了Host-Parasitoid模型.该模型是一类非线性离散系统,反映了在一定的时间和空间内,寄生虫和寄宿主之间的生存状态.通过调节各种影响下的分岔参数,可以观察到系统具有周期泡,倍周期分叉,间歇混沌和Hopf分岔等复杂非线性动力学现象,揭示了系统通向混沌的途径.利用不同周期遍历下的奇怪吸引子和具有分形边界的吸引盆对系统的非线性特性进行了深入的探讨.最后利用参数开闭环控制法对系统的混沌状态进行了有效的控制.数值仿真和理论分析表明,选择相应的控制参数可将该系统的混沌状态控制到不同的稳定周期运动.     

同步发电机混沌振荡的精确线性化控制

在周期性负荷扰动情况下,同步发电机可能诱发混沌振荡现象,严重威胁电网运行安全性;为解决此问题,采用精确线性化控制方法来设计混沌控制器;首先,系统的数学模型经过状态变换,对非线性系统进行线性化处理,然后结合配置反馈增益方法,设计出相应控制器;仿真结果表明,所设计的控制器能够有效抑制混沌振荡,发电机转子运行角和发电机相对转速由无规则的运动转变为稳定运行,提高了电力系统稳定性。     

非线性迭代学习控制问题的延拓修正牛顿法

对于非线性迭代学习控制问题,提出基于延拓法和修正Newton法的具有全局收敛性的迭代学习控制新方法.由于一般的Newton型迭代学习控制律都是局部收敛的,在实际应用中有很大局限性.为拓宽收敛范围,该方法将延拓法引入迭代学习控制问题,提出基于同伦延拓的新的Newton型迭代学习控制律,使得初始控制可以较为任意的选择.新的迭代学习控制算法将求解过程分成N个子问题,每个子问题由换列修正Newton法利用简单的递推公式解出.本文给出算法收敛的充分条件,证明了算法的全局收敛性.该算法对于非线性系统迭代学习控制具有全局收敛和计算简单的优点.     

A new adaptive mutative scale chaos optimization algorithm and its application

Based on results of chaos characteristics comparing one-dimensional iterative chaotic self-map x = sin(2/x) with infinite collapses within the finite region[-1;1] to some representative iterative chaotic maps with finite collapses (e.g., Logistic map, Tent map, and Chebyshev map), a new adaptive mutative scale chaos optimization algorithm (AMSCOA) is proposed by using the chaos model x = in(2/x). In the optimization algorithm, in order to ensure its advantage of speed convergence and high precision in the seeking optimization process, some measures are taken: 1) the searching space of optimized variables is reduced continuously due to adaptive mutative scale method and the searching precision is enhanced accordingly; 2) the most circle time is regarded as its control guideline. The calculation examples about three testing functions reveal that the adaptive mutative scale chaos optimization algorithm has both high searching speed and precision.