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Found 8 papers, 4 papers with code
Secure Set-Based State Estimation for Linear Systems under Adversarial Attacks on Sensors
When a strategic adversary can attack multiple sensors of a system and freely choose a different set of sensors at different times, how can we ensure that the state estimate remains uncorrupted by the attacker?
Sensor Fault Detection and Isolation in Autonomous Nonlinear Systems Using Neural Network-Based Observers
The proposed sensor fault detection and isolation (s-FDI) method applies to a general class of nonlinear systems.
Parameterization-Free Observer Design for Nonlinear Systems: Application to the State Estimation of Networked SIR Epidemics
In this paper, we present an observer design approach for estimating the state of nonlinear systems, without requiring any parameterization of the system's nonlinearities.
Resilient Set-based State Estimation for Linear Time-Invariant Systems Using Zonotopes
This paper considers the problem of set-based state estimation for linear time-invariant (LTI) systems under time-varying sensor attacks.
Robust Data-Driven Predictive Control of Unknown Nonlinear Systems using Reachability Analysis
By using the past noisy input-output data in the learning phase, we propose a novel method to over-approximate reachable sets of an unknown nonlinear system.
Secure State Estimation against Sparse Attacks on a Time-varying Set of Sensors
At each time step, the local estimates of sensors are fused by solving an optimization problem to obtain a secure estimation, which is then followed by a local detection-and-resetting process of the decentralized observers.
Learning-based Design of Luenberger Observers for Autonomous Nonlinear Systems
Designing Luenberger observers for nonlinear systems involves the challenging task of transforming the state to an alternate coordinate system, possibly of higher dimensions, where the system is asymptotically stable and linear up to output injection.
Data-driven Set-based Estimation of Polynomial Systems with Application to SIR Epidemics
The offline phase utilizes past input-output data to estimate a set of possible coefficients of the polynomial system.
