A physics-informed neural network learns time-varying safe tubes encoding full STL specifications, and a closed-form controller confines unknown Euler-Lagrange systems within them under input constraints.
Accelerated training of physics-informed neural networks (pinns) using meshless discretizations
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Learning Spatiotemporal Tubes for Full Class of Signal Temporal Logic Tasks for Control of Unknown Systems under Input Constraints
A physics-informed neural network learns time-varying safe tubes encoding full STL specifications, and a closed-form controller confines unknown Euler-Lagrange systems within them under input constraints.