Scientific Python (SciPy) based Simulation and Control of Underactuated Robotic System
Harsimran Singh Mavi, Rajnish Mallick, Ashish Singla · 2023
This tutorial describes scientific python (SciPy) for solving ordinary differential equations (ODEs) appearing in diverse physical systems and a line-by-line explanation of the working codes for engineering and science students and practitioners. For better understanding, an engineering case study is considered in detail to explain the SciPy implementation. The case study belongs to a highly challenging, unstable and nonlinear underactuated system: rotary inverted pendulum (RIP). The current tutorial presents both SciPy simulations along with an experimental investigation of the RIP system. The analytical and experimental results show a good match with a maximum per cent error of the order of 10-4 units. Elapsed computational times are also compared between contemporary scientific computing platforms, such as MATLAB and SciPy. In the computational experimental trials of RIP system, it is found that the SciPy code has 84% faster computational time as compared to the same code being executed in the MATLAB environment. The executable codes are available for educational and research purposes at https://github.com/hmavi/SciPy_Tutorial/blob/main/Rotary_Inverted_Pendulum.py.