Data underlying the PhD thesis: Learning-based control under constraints: Towards safety and computational efficiency

This dataset supports the PhD thesis titled <em>"Learning-Based Control Under Constraints: Towards Safety and Computational Efficiency"</em>. The thesis comprises six main chapters (Chapters 2–7), and the data is organized accordingly. All simulations were conducted in a MATLAB environment.<strong>Chapters 2–3</strong> focus on constrained approximate dynamic programming (ADP) algorithms for safe control. In particular, Chapter 2 presents a convex piecewise quadratic optimization algorithm designed to efficiently solve the ADP problem. Chapter 3 uses penalty methods to deal with constraints.<strong>Chapter 4</strong> includes code for the explicit approximation of safety filters.<strong>Chapter 5</strong> implements all-element predictive safety filters to ensure the safe control of piecewise affine (PWA) systems.<strong>Chapters 6–7</strong> propose an integrated optimization- and learning-based control framework for general constrained nonlinear systems.<br>