SP-ICL integrates L1 regularization with integral concurrent learning using sliding modes to recover sparse parameters online and proves ultimate boundedness of closed-loop trajectories via non-smooth Lyapunov analysis.
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math.OC 2years
2026 2verdicts
UNVERDICTED 2representative citing papers
A DMD-based method trains a predictive model on known-parameter data to estimate unknown parameters in control-affine nonlinear systems, with accurate recovery shown on the controlled Duffing oscillator.
citing papers explorer
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Adaptive Control with Sparse Identification of Nonlinear Dynamics
SP-ICL integrates L1 regularization with integral concurrent learning using sliding modes to recover sparse parameters online and proves ultimate boundedness of closed-loop trajectories via non-smooth Lyapunov analysis.
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A Dynamic Mode Decomposition Approach to Parameter Identification
A DMD-based method trains a predictive model on known-parameter data to estimate unknown parameters in control-affine nonlinear systems, with accurate recovery shown on the controlled Duffing oscillator.