In this article, we consider a backward problem in time of the diffusion equation with local and nonlocal operators. This inverse problem is ill-posed because the solution does not depend continuously on the measured ...In this article, we consider a backward problem in time of the diffusion equation with local and nonlocal operators. This inverse problem is ill-posed because the solution does not depend continuously on the measured data. Inspired by the classical Landweber iterative method and Fourier truncation technique, we develops a modified Landweber iterative regularization method to restore the continuous dependence of solution on the measurement data. Under the a-priori and a-posteriori choice rules for the regularized parameter, the convergence estimates for the regularization method are derived. Some results of numerical simulation are provided to verify the stability and feasibility of our method in dealing with the considered problem.展开更多
为保持系统在执行器失效故障时仍具有较高的可靠性以及所期望的动态特性,针对一类基于T-S模糊模型的非线性不确定时滞网络控制系统(NCSs:Networked Control Systems),进行了鲁棒H∞容错控制问题研究。在考虑带有量化误差的非理想网络环...为保持系统在执行器失效故障时仍具有较高的可靠性以及所期望的动态特性,针对一类基于T-S模糊模型的非线性不确定时滞网络控制系统(NCSs:Networked Control Systems),进行了鲁棒H∞容错控制问题研究。在考虑带有量化误差的非理想网络环境下,应用并行分配补偿(PDC:Parallel Distributed Compensation)算法,建立闭环系统的全局模糊模型;通过构造时滞依赖的Lyapunov函数,采用Jensen不等式以及引入自由权矩阵,得到闭环系统鲁棒H∞容错控制器的存在条件,并将控制器的设计转化为求解一组线性矩阵不等式的凸优化问题。仿真算例表明了该方法的有效性。展开更多
基金supported by the NSF of Ningxia(2022AAC03234)the NSF of China(11761004),the Construction Project of First-Class Disciplines in Ningxia Higher Education(NXYLXK2017B09)the Postgraduate Innovation Project of North Minzu University(YCX23074).
文摘In this article, we consider a backward problem in time of the diffusion equation with local and nonlocal operators. This inverse problem is ill-posed because the solution does not depend continuously on the measured data. Inspired by the classical Landweber iterative method and Fourier truncation technique, we develops a modified Landweber iterative regularization method to restore the continuous dependence of solution on the measurement data. Under the a-priori and a-posteriori choice rules for the regularized parameter, the convergence estimates for the regularization method are derived. Some results of numerical simulation are provided to verify the stability and feasibility of our method in dealing with the considered problem.
文摘为保持系统在执行器失效故障时仍具有较高的可靠性以及所期望的动态特性,针对一类基于T-S模糊模型的非线性不确定时滞网络控制系统(NCSs:Networked Control Systems),进行了鲁棒H∞容错控制问题研究。在考虑带有量化误差的非理想网络环境下,应用并行分配补偿(PDC:Parallel Distributed Compensation)算法,建立闭环系统的全局模糊模型;通过构造时滞依赖的Lyapunov函数,采用Jensen不等式以及引入自由权矩阵,得到闭环系统鲁棒H∞容错控制器的存在条件,并将控制器的设计转化为求解一组线性矩阵不等式的凸优化问题。仿真算例表明了该方法的有效性。
