Discrete-time distributed control and fault diagnosis for a class of linear systems

Abstract

This paper presents a solution to the problem of decentralized control, fault detection and isolation for teams of cooperative autonomous mobile vehicles. The strategy is carried out in the discrete time domain. A local observer is used by each agent to estimate the overall state of the team. This estimate is, then, used both to compute its local control input and isolate faulty teammates, even in absence of direct communication with them. For diagnosis purposes, a set of residual vectors, each of them sensible to a fault occurring on a single vehicle, is designed and an adaptive threshold is derived in order to avoid false alarms. The approach is validated via numerical simulations involving 4 vehicles moving in formation in a 3D environment

Distributed Infinite-Horizon Optimal Control of Discrete-Time Linear Systems over Networks

“…In this paper we focus on the distributed optimal control problem of discrete-time linear stochastic systems with Gaussian noise over sensor networks. A distributed controller is composed of local control stations which receive some measurement data from the plant process and regulates a portion of the input signal by exchanging data among its neighbors and without the need of converging some information in specific points of the network ( [40], [21], [35], [28], [16]). In particular, we adopt the distributed discretetime framework where the neighboring nodes are able to communicate with some intermediate steps between two time instant (e.g., [1], [31], [17], [32]).…”

Attack-aware multi-sensor integration algorithm for autonomous vehicle navigation systems

“…For this reason, it is challenging to generate robust residuals that are insensitive to noise and arXiv:1709.02456v1 [math.OC] 7 Sep 2017 uncertainties yet sensitive to attacks in order to provoke a quick alarm [17]. Optimal filters and state observers have been proposed to generate a sequence of residuals that resemble white noise in normal operation [18], [19]. After residual generation, an attack alarm will be triggered at the moment residuals exceed the threshold.…”