Open AccessRobust finite‐frequency filter design for linear uncertain systems using polynomially parameter‐dependent approach
Author(s) -
Ren Yingying,
Li Qing,
Ding DaWei,
Kang Wen
Publication year - 2020
Publication title -
iet control theory and applications
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.059
H-Index - 108
eISSN - 1751-8652
pISSN - 1751-8644
DOI - 10.1049/iet-cta.2019.0600
Subject(s) - control theory (sociology) , filter design , filter (signal processing) , mathematics , attenuation , noise (video) , convex optimization , computer science , mathematical optimization , regular polygon , physics , geometry , control (management) , artificial intelligence , optics , image (mathematics) , computer vision
This study investigates the problem of robust filter design for continuous‐time linear uncertain systems affected by external noises in finite‐frequency (FF) ranges. The objective is to design an admissible filter guaranteeing asymptotic stability of the filtering error system with a prescribed FF noise attenuation level. To this end, homogenous polynomially parameter‐dependent Lyapunov functions are used to assess the stability of the filtering error system, and robust FF bounded realness lemma is used to describe the noise attenuation specifications. Polynomially parameter‐dependent matrices and some scalars are introduced to facilitate filter design and reduce conservatism. Moreover, a sequential convex approximation method is used to replace the non‐convex constrained set with a convex feasible one. On this basis, an iterative algorithm is developed to calculate the filter parameters. It is demonstrated that the proposed robust FF filter can achieve a better noise attenuation performance in the FF range than the existing ones in the literature. An example about F‐18 aircraft model is given to illustrate the effectiveness of the proposed method.