广义非线性鲁棒能量-峰值滤波器用于微分代数系统
Generalized Nonlinear Robust Energy-to-Peak Filtering for Differential Algebraic Systems
AI总结：
本文针对具有模型不确定性的非线性描述系统鲁棒非线性能量-峰值滤波问题，提出广义非线性动态滤波结构，通过半定规划和严格LMIs设计L2-Linfty滤波器以优化能量-峰值性能。
摘要：
本文研究了具有模型不确定性的非线性描述系统鲁棒非线性能量-峰值滤波问题。系统假设状态和输出方程中存在非线性项，以及实现矩阵中的规范有界时变不确定性。针对此类系统，提出了一种具有比传统静态增益和动态滤波结构更多自由度的广义非线性动态滤波结构。通过半定规划和严格LMIs设计L2-Linfty滤波器，以优化能量-峰值滤波性能。
英文摘要：
The problem of robust nonlinear energy-to-peak filtering for nonlinear descriptor systems with model uncertainties is addressed. The system is assumed to have nonlinearities both in the state and output equations as well as norm-bounded time-varying uncertainties in the realization matrices. A generalized nonlinear dynamic filtering structure is proposed for such a class of systems with more degrees of freedom than the conventional static-gain and dynamic filtering structures. The L2-Linfty filter is synthesized through semidefinite programming and strict LMIs, in which the energy-to-peak filtering performance in optimized.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
