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Backup Plan Constrained Model Predictive Control with Guaranteed Stability
To include this new safety concept in control problems, we formulate a feasibility maximization problem aiming to maximize the feasibility of the primary and alternative missions.
Certified Robust Control under Adversarial Perturbations
Autonomous systems increasingly rely on machine learning techniques to transform high-dimensional raw inputs into predictions that are then used for decision-making and control.
Constrained Attack-Resilient Estimation of Stochastic Cyber-Physical Systems
In this paper, a constrained attack-resilient estimation algorithm (CARE) is developed for stochastic cyber-physical systems.
Backup Plan Constrained Model Predictive Control
To incorporate this new safety concept in control problems, we formulate a feasibility maximization problem that adopts additional (virtual) input horizons toward the alternative missions on top of the input horizon toward the primary mission.
