Distributed dissipative filtering for flexible manipulator with randomly occurring uncertainties and missing data

Abstract

Purpose The purpose of this paper is to investigate the dissipative filtering problem for a flexible manipulator (FM) with randomly occurring uncertainties and randomly occurring missing data. Design/methodology/approach The randomly occurring phenomena during the filtering procedure are described by Bernoulli sequences. Based on the idea of dissipative theory, the distributed filtering error augmented system is derived for ensuring the prescribed dissipative performance. Findings By constructing appropriate Lyapunov function, sufficient dissipative filtering conditions are derived such that the filtering error can be approaching zero. Then, the desired distributed filter gains are designed with the help of matrix transformation. Originality/value The merit of this paper is proposing a novel distributed filtering framework for an FM with external disturbance under the dissipative framework, which can provide a more applicable filter design.