基于Duffing振子的天然气管道泄漏检测方法

针对天然气管道泄漏因泄漏声波信号信噪比(SNR)过低而难于检测的问题,研究了基于Duffing振子的天然气管道泄漏检测方法。该方法将待检测数据输入Duffing振子系统,以振子系统的状态转化实现非周期信号中周期信号的检测。为了更好地提高Duffing振子的检测性能,在Duffing振子设计阶段,以随机共振的有关理论为基础,通过对系统输出信噪比的优化来实现Duffing振子的参数设计。基于实际天然气管道泄漏数据的测试结果表明,所提出方法可在低信噪比(-68dB)的情况下有效检测出泄漏,具有较好的检测性能。     

驱动输入白噪声对Duffing振子运动影响分析

强噪声背景下混沌弱信号检测是利用弱信号的周期扰动使系统运动状态发生改变实现的，研究了数值解算时计算步长和驱动输入白噪声对弱信号检测中Duffing振子运动特征的影响，重点研究了对Duffing振子混沌临界态和大尺度周期态的影响，结果表明采用数值解算的步长不同系统运动状态不相同，与统计意义下任何零均值噪声都不会改变系统原有运行轨迹不同，不同功率的驱动输入白噪声会导致系统状态改变，分析了产生原因。     

基于耦合Duffing振子的微弱故障信号检测

针对传统信号处理方法在低信噪比条件下对微弱信号检测的不足,提出一种对双Duffing振子进行阻尼项耦合的方法,通过对此系统进行动力学分析,比单个Duffing振子具有更加复杂的动力学行为。阐述了基于相平面变化的微弱信号检测原理,对时间进行尺度的变换,实现了未知频率信号的检测,最后对微弱脉冲信号进行检测以及真实的故障轴承的早期诊断,取得了较好的效果,该方法在无线通信、雷达系统、旋转机械早期故障诊断等领域具有广阔的前景。     

一类分数阶分段Duffing振子的混沌研究

研究了谐波激励下含有分数阶微分项的分段Duffing振子的混沌运动,分数阶微分项采用Caputo定义进行计算,并利用等效刚度和等效阻尼的概念对其进行处理。运用Melnikov方法,建立了Smale马蹄意义下混沌运动的必要条件,得到了系统发生混沌运动的临界条件,并进行了解析解和数值解的比较,结果证明了解析必要条件的正确性。最后通过数值模拟,研究了系统线性刚度系数、阻尼系数、分数阶阶次、分数阶系数以及分段Duffing刚度系数对系统混沌运动的影响。     

基于Duffing振子的BPSK载波信号检测方法研究

针对低压配电网具有噪声干扰强、信号衰减大等问题,提出了用Duffing振子来检测BPSK载波信号的新方法.Duffing振子对微弱信号敏感,信号的不同相位将引起系统在混沌态与大尺度周期态之间的相变,该方法就是利用载波信号的相位引起的Duffing振子的相变,通过对该相变的判别来检测载波信号的相位信息.同时还分析了Duf...     

摩擦振子的混沌随机运动

摩擦振子的混沌随机运动冯奇（同济大学）１．引言在机械系统中常常可遇所谓的“ＳｔｉＣｋ－Ｓｌｉｐ”问题，它们是产生工业噪声的重要振源之一。例如：关门时发出的嘎嘎声；制动时的刺耳响声；车床切削时发出的轰鸣；火车通过小半径弧形轨道时的尖叫；乃至振动着的琴弦...     

非线性随机动力系统的最优多项式控制

根据物理随机最优控制理论,发展了适用于一般非线性随机动力系统的最优多项式控制策略,考察了随机地震动作用下不同非线性水平Duffing系统的随机最优控制。结果表明,受控后系统反应的离散性大大降低、系统性态显著改善;采用能量均衡的超越概率准则,1阶线性控制器可以达到高阶非线性控制器的控制效果,这对于非线性控制器可能导致系统不稳定的场合具有重要意义。此外,相比较基于统计线性化的LQG控制,发展的非线性随机最优控制策略对Duffing系统的非线性水平不敏感、具有良好的鲁棒性,能实现系统的精细化控制,而采用名义白噪声输入的LQG控制则不具备这一特点。     

基于Melnikov方法的分数阶Duffing振子混沌阈值解析研究

研究了含有分数阶微分项的Duffing振子的分岔与混沌行为,利用等效刚度和等效阻尼的概念对分数阶微分项进行处理,将分数阶微分项等效成三角函数与指数函数的形式,用Melnikov方法分析了分数阶Duffing振子产生分岔与混沌的必要条件,得到了其解析结果.进行了解析解和数值解的比较,证明了解析结果的精确度,并通过仿真计算...     

非平稳地震动过程模拟的谱表示-随机函数方法

在Priestley演变谱理论的基础上,采用随机函数的思想,建议了一类新的全非平稳过程模拟的谱表示-随机函数方法。在谱表示-随机函数方法中,实现了用2个基本随机变量即可精确表达原随机过程的目的。通过选取基本随机变量的离散代表点集,可以直接由演变功率谱密度函数生成具有给定赋得概率的代表性样本集合。以全非平稳地震动加速度过程的演变功率谱为例,验证了本文方法的有效性和优越性。最后,结合概率密度演化方法,进行了Duffing振子的随机地震反应分析与抗震可靠度计算。     

分数阶Duffing振子的亚谐共振

研究了含分数阶微分项的Duffing振子的亚谐共振,利用平均法得到了系统的一阶近似解。提出了亚谐共振时等效线性阻尼和等效线性刚度的概念,分析了分数阶微分项的系数和阶次对系统动力学特性的影响。建立了亚谐共振定常解的幅频曲线的解析表达式,并得到了亚谐共振周期响应的存在条件和稳定性判断准则。最后进行了数值解和解析解的比较,证明了解析结果的准确性,并通过数值仿真研究了分数阶微分项的参数对亚谐共振解的存在条件、稳定性条件和系统幅频曲线的影响。     

Phase increment analysis of damped Duffing oscillators

A phase increment method is introduced to construct the response curves for the damped Duffing oscillator in primary, superharmonic, and subharmonic resonances. Non-linear parameters can be arbitrarily large. The algorithm is numerically stable. All resonance response curves are constructed in a unified manner. Closed loop curves are obtained in subharmonic resonances as opposed to open ended ones predicted by the perturbation method. Higher order resonances are constructed without difficulties. Loops are also observed in superharmonic resonances when non-linearity is not small.     

Nonlinear stochastic optimal control of Preisach hysteretic systems

The nonlinear stochastic optimal control of Preisach hysteretic systems is studied, and the control procedure is illustrated with an example of the single-degree-of-freedom Preisach system. The Preisach hysteretic system subjected to a stochastic excitation is first replaced by an equivalent non-hysteretic nonlinear stochastic system with displacement-amplitude-dependent damping and stiffness, by using the generalized harmonic balance technique. Then, the relationship between the displacement amplitude and total system energy is established, and the equivalent damping and stiffness coefficients are expressed as functions of the system energy. The averaged Itô stochastic differential equation for the system energy as one-dimensional controlled diffusion process, is derived by using the stochastic averaging method of energy envelope. For the semi-infinite time-interval ergodic control, the dynamical programming equation is obtained based on the stochastic dynamical programming principle, and is solved to yield the optimal control force. Finally, the Fokker–Planck–Kolmogorov equation associated with the averaged Itô equation is established, and the stationary probability density of the system energy is obtained, from which the variances of the controlled system response and the optimal control force are predicted and the control efficacy is evaluated. Numerical results show that the proposed control strategy for Preisach hysteretic systems is very effective and efficient.     

Quality control by the optimal control of a discrete-state stochastic process

This paper provides a stochastic control approach to quality control. Results and numerical examples are used to assess the mutual effects of the costs of inspection sampling and the failure of units that have been sold. The approach is an extension of classical statistical quality-control procedures. Firstly, the time dimension in production is explicitly considered and secondly, non-constants, such as variations in production output, production reliability, etc., with lines, are used in formulating the problems. These problems are then resolved analytically for linear inspection and failure costs and numerically for non-linear costs.     

Combining stochastic programming and optimal control to decompose multistage stochastic optimization problems

The paper suggests a possible cooperation between stochastic programming and optimal control for the solution of multistage stochastic optimization problems. We propose a decomposition approach for a class of multistage stochastic programming problems in arborescent form (i.e. formulated with implicit non-anticipativity constraints on a scenario tree). The objective function of the problem can be either linear or nonlinear, while we require that the constraints are linear and involve only variables from two adjacent periods (current and lag 1). The approach is built on the following steps. First, reformulate the stochastic programming problem into an optimal control one. Second, apply a discrete version of Pontryagin maximum principle to obtain optimality conditions. Third, discuss and rearrange these conditions to obtain a decomposition that acts both at a time stage level and at a nodal level. To obtain the solution of the original problem we aggregate the solutions of subproblems through an enhanced mean valued fixed point iterative scheme.     

The stochastic optimal model of continuous production process control

This work is the result of an investigation undertaken by the author during his stay in the U.S.S.R. The elaborated algorithm of electrolysis process control proved to be effective and the calculating procedure uncomplicated.

This approach may be used for analysing and designing control systems in a wide class of continuous processes, which are dealt with in investigating activities, in the manufacturing sphere and information exchange, etc.     

Time-delay stochastic optimal control and stabilization of quasi-integrable Hamiltonian systems

Innovative procedures for the time-delay stochastic optimal control and stabilization of quasi-integrable Hamiltonian systems subject to Gaussian white noise excitations are proposed. First, the problem of time-delay stochastic optimal control of quasi-integrable Hamiltonian systems is formulated and converted into the problem of stochastic optimal control without time delay. Then the converted control problem is solved by applying the stochastic averaging method for quasi-integrable Hamiltonian systems and the stochastic dynamical programming principle. The time-delay feedback stabilization of quasi-integrable Hamiltonian systems is formulated as an ergodic control problem with an un-determined cost function which is determined later by minimizing the largest Lyapunov exponent of the controlled system. As an example, a two-degree-of-freedom quasi-integrable Hamiltonian system with time-delay feedback control forces is investigated in detail to illustrate the procedures and their effectiveness.     

Effect of variation of input banwidth on the response of hardening Duffing oscillators

The response of hardening Duffing oscillators to coloured noise excitation is considered. It is shown that for certain combinations of excitation intensity and bandwidth the system realises multi-valued response states. Theoretical predictions of bounds in the parameter space which define regions of multiple statistical moments are supported by numerical simulation results. The effect of the occurrence and persistence of multi-level responses on the probability distribution of the peaks is also considered.     

基于精细积分的瞬时最优控制算法

对于实时控制中测量得到的等间距离散信号，可合理地认为其在每个时间间隔内线性变化。通过在瞬时最优控制算法中用精确积分代替以往采用的近似积分公式，从而给出了精细瞬时最优控制算法，包括精细瞬时闭环最优控制，精细瞬时开环最优控制和精细瞬时开闭环最优控制。这些算法具有精细积分高精度的特点，对于时间步长较大的情况仍可给出比拟于精确解的数值结果。三种算法虽然形式不同，但在理想控制环境下其控制效果完全相同。数值算例表明了本文算法高精度及有效性。     

地震激励下20层钢结构基准模型的非线性随机最优控制

建筑结构基准问题常用来比较各种振动控制策略的优劣。运用基于拟哈密顿系统随机平均法与随机动态规划原理的非线性随机最优(NSO)控制策略,研究了地震激励下20层钢结构基准模型的振动控制。建立基准模型的系统运动方程,通过模态变换转换到模态坐标下进行研究。由于结构的状态只有部分是可观测的,可通过分离原理将部分观测问题转化成完全可观测问题,由Kalman滤波方法得到系统状态的条件均值。运用拟可积Hamil-ton系统随机平均法得到随机平均方程,对部分模态进行控制求解。通过求解动态规划方程得到非线性的最优控制力,对结构的响应进行控制。将NSO控制得到的性能评价指标与线性二次型高斯(LQG)最优控制得到的评价指标进行对比,发现该非线性随机最优控制策略更加有效。