运用随机平均法研究了宽带噪声激励下带有分数阶PI~λD~μ控制器的强非线性系统.首先,应用广义谐波平衡技术,将分数阶PI~λD~μ控制力分解为幅值依赖的等效拟线性阻尼力和拟线性回复力,得到了受控整数阶等效非线性系统.然后,运用基于广...运用随机平均法研究了宽带噪声激励下带有分数阶PI~λD~μ控制器的强非线性系统.首先,应用广义谐波平衡技术,将分数阶PI~λD~μ控制力分解为幅值依赖的等效拟线性阻尼力和拟线性回复力,得到了受控整数阶等效非线性系统.然后,运用基于广义谐和函数的随机平均法得到关于幅值的平均伊藤微分方程.最后,建立并求解相应的简化Fokker-Planck-Kolmogorov(FPK)方程,得到稳态概率密度函数.作为算例,考察了Duffing-van de Pol振子.数值结果表明随机平均法能够达到较高的精度,分数阶PI~λD~μ控制器能够对系统响应进行有效的控制.此外,宽带噪声参数ξ_i、ω_i及D_i改变时,本文提出的方法仍具有较好的适用性,分数阶控制器仍同样具有非常好的控制效果.展开更多
Several algorithms were proposed relating to the development of a framework of the perturbation-based stochastic finite element method (PSFEM) for large variation nonlinear dynamic problems. For this purpose, algorith...Several algorithms were proposed relating to the development of a framework of the perturbation-based stochastic finite element method (PSFEM) for large variation nonlinear dynamic problems. For this purpose, algorithms and a framework related to SFEM based on the stochastic virtual work principle were studied. To prove the validity and practicality of the algorithms and framework, numerical examples for nonlinear dynamic problems with large variations were calculated and compared with the Monte-Carlo Simulation method. This comparison shows that the proposed approaches are accurate and effective for the nonlinear dynamic analysis of structures with random parameters.展开更多
文摘运用随机平均法研究了宽带噪声激励下带有分数阶PI~λD~μ控制器的强非线性系统.首先,应用广义谐波平衡技术,将分数阶PI~λD~μ控制力分解为幅值依赖的等效拟线性阻尼力和拟线性回复力,得到了受控整数阶等效非线性系统.然后,运用基于广义谐和函数的随机平均法得到关于幅值的平均伊藤微分方程.最后,建立并求解相应的简化Fokker-Planck-Kolmogorov(FPK)方程,得到稳态概率密度函数.作为算例,考察了Duffing-van de Pol振子.数值结果表明随机平均法能够达到较高的精度,分数阶PI~λD~μ控制器能够对系统响应进行有效的控制.此外,宽带噪声参数ξ_i、ω_i及D_i改变时,本文提出的方法仍具有较好的适用性,分数阶控制器仍同样具有非常好的控制效果.
文摘Several algorithms were proposed relating to the development of a framework of the perturbation-based stochastic finite element method (PSFEM) for large variation nonlinear dynamic problems. For this purpose, algorithms and a framework related to SFEM based on the stochastic virtual work principle were studied. To prove the validity and practicality of the algorithms and framework, numerical examples for nonlinear dynamic problems with large variations were calculated and compared with the Monte-Carlo Simulation method. This comparison shows that the proposed approaches are accurate and effective for the nonlinear dynamic analysis of structures with random parameters.