Proposes a subspace classification approach using a nullspace-based filter for data-driven fault isolation in LTI systems, independent of explicit models.
Behavioral systems theory in data-driven analysis, signal processing, and control,
2 Pith papers cite this work. Polarity classification is still indexing.
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The authors adapt closed-loop and IRL parameterizations to continuous time, deriving policy iteration schemes, a data-driven CARE, convex reformulations, and a policy gradient flow while unifying the two approaches.
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Data-Driven Fault Isolation in Linear Time-Invariant Systems: A Subspace Classification Approach
Proposes a subspace classification approach using a nullspace-based filter for data-driven fault isolation in LTI systems, independent of explicit models.
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Data-Driven Continuous-Time Linear Quadratic Regulator via Closed-Loop and Reinforcement Learning Parameterizations
The authors adapt closed-loop and IRL parameterizations to continuous time, deriving policy iteration schemes, a data-driven CARE, convex reformulations, and a policy gradient flow while unifying the two approaches.