Resilient time-varying output formation tracking of heterogeneous linear multiagent systems under malicious false data injection attacks and denial-of-service attacks over digraphs

• Main Authors: Feng, Zhi, Hu, Guoqiang
• Other Authors: School of Electrical and Electronic Engineering
• Format: Article
• Language: English
• Published: 2023
• Subjects: Engineering::Electrical and electronic engineering; Digraphs; Exponential Convergence
• Online Access: https://hdl.handle.net/10356/168888
• Institution: Nanyang Technological University

A distributed control fashion of cooperative formation tracking may be vulnerable to malicious attacks on sensors and communications that deteriorate the formation tracking performance or even destabilize the entire multiagent system. This article addresses a resilient time-varying output formation tracking problem of linear heterogeneous multiagent systems, where an attacker can adversely inject false data injection (FDI) attacks on sensors and Denial-of-Service (DoS) attacks on communications. Both characteristics will not only enhance the practical relevance of the studied issue, but also bring nontrivial design challenges of distributed control algorithms and convergence analysis. A novel resilient distributed control architecture is developed to guarantee a global exponential time-varying output formation tracking. In particular, the design includes features: (1) a resilient distributed leader estimator is developed to estimate the leader's state for each follower under DoS attacks over digraphs; (2) a distributed output feedback controller integrated with an observer-based resilient mechanism is developed to achieve the time-varying output formation tracking under attacks; (3) unlike existing related works to handle attacks as bounded disturbances or faults, the proposed design is resilient to enable exponential convergence, whereas many related works obtain uniformly ultimately boundedness (UUB) convergence. Simulation results are presented to validate the design's effectiveness.