Python Code and Data Supporting Chapter 3 of the PhD Thesis: Temporally Smoothed Cascaded Online Learning Flight Control

The dataset contains relevant Python code and supporting data in relation to CHAPTER 3 of the thesis Safe and Sample Efficient Reinforcement Learning for Flight Control by Yifei Li (2026). The thesis aims to develop reliable and efficient online and offline actor-critic-based policy optimization algorithms for data-driven tracking control applications. This chapter studies the benefits of using temporal policy smoothness regularization and low-pass filter techniques for the cascaded online learning flight control. The code provides a simulation framework for the flight control system and enables the visualization of action-smoothing techniques. The PyTorch package serves as the main instrument for simulation. For more information, we refer to the thesis chapter.