Consensus of networked double integrator systems under sensor bias

A novel distributed control law for consensus of networked double integrator systems with biased measurements is developed in this article. The agents measure relative positions over a time-varying, undirected graph with an unknown and constant sensor bias corrupting the measurements. An adaptive co...

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Bibliographic Details
Published in:arXiv.org 2022-04
Main Authors: Sinha, Pallavi, Sukumar, Srikant, Sinhmar, Himani
Format: Article
Language:English
Subjects:
Adaptive control
Algorithms
Bias
Control theory
Double integrators
Excitation
Integrators
Sensors
Online Access:Get full text
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Summary:A novel distributed control law for consensus of networked double integrator systems with biased measurements is developed in this article. The agents measure relative positions over a time-varying, undirected graph with an unknown and constant sensor bias corrupting the measurements. An adaptive control law is derived using Lyapunov methods to estimate the individual sensor biases accurately. The proposed algorithm ensures that position consensus is achieved exponentially in addition to bias estimation. The results leverage recent advances in collective initial excitation based results in adaptive estimation. Conditions connecting bipartite graphs and collective initial excitation are also developed. The algorithms are illustrated via simulation studies on a network of double integrators with local communication and biased measurements.
ISSN:2331-8422