Python Control Systems 2: State Space Models, Responses, Discretization, and Basic Operations

#controltheory #controlengineering #mechatronics #robotics #machinelearning #mechanicalengineering #electricalengineering #datascientist #dynamicalsystems #dynamics It takes a significant amount of time and energy to create these free video tutorials. You can support my efforts in this way: Buy me a Coffee: https://www.buymeacoffee.com/Aleksand... PayPal: https://www.paypal.me/AleksandarHaber Patreon: https://www.patreon.com/user?u=320801... You Can also press the Thanks YouTube Dollar button In this control engineering and control theory tutorial, we explain how to define and simulate state-space models of linear dynamical systems in Python. Furthermore, we explain how to perform basic operations on state-space models in Python. The approach presented in this webpage tutorial is based on the Python Control Systems Library. More precisely, in this webpage tutorial, we explain (1) How to define state-space models in Python. (2) How to convert state-space models to transfer function models and back in Python. (3) How to simulate the step response of state-space models in Python. (4) How to compute poles, zeros, natural frequencies, and damping ratios of state-space models in Python. (5)How to discretize continuous-time state-space models in Python.