Distributed H∞ Consensus Filtering for Parabolic Distributed Parameter Systems with Multiple Missing Measurements: A Mobile Sensing Approach

• Published in: Journal of control science and engineering 2023-02, Vol.2023, p.1-17
• Main Authors: Qian, Xueming, Cui, Baotong
• Format: Article
• Language: English
• Subjects: Conditional probability; Constraint modelling; Distributed parameter systems; Energy consumption; Filtration; H infinity; Missing data; Parameter estimation; Partial differential equations; Remote sensors; Sensors; Wireless sensor networks
• ISSN: 1687-5249; 1687-5257
• DOI: 10.1155/2023/9740248

This paper investigates the distributed H∞ consensus filtering issue for a class of distributed parameter systems with bounded disturbance. In a framework of optimizing performance, a new approach to improving filter performance is proposed by employing mobile sensor networks. Moreover, the information missing in mobile sensor networks is modeled as a conditional probability distribution. The aim of the filtering challenge is to construct a distributed consensus filter such that the filtering error system is globally asymptotically stable in the mean square, and what disturbances do to the estimation accuracy is attenuated at the H∞ consensus performance level. Utilizing the Lyapunov direct approach and the spatial operator technique, several sufficient criteria are given for the proposed filter to satisfy the H∞ consensus performance constraint. Finally, a numerical simulation is given to demonstrate the effectiveness of the design scheme of the proposed filter.