Chaos Annihilation-Based on Genetic Algorithms in a Non-smooth Air-gap Permanent Magnet Synchronous Motor Embedded in the Microcontroller

This paper is devoted to the dynamical probing, microcontroller execution, and chaos annihilation based on genetic algorithms (GAs) in a non-smooth air-gap permanent magnet synchronous motor (NSAGPMSM) without external disturbances. The numerical simulations of NSAGPMSM in the absence of external disturbances reveal the existence of two different shapes of chaotic characteristics, reverse period doubling and periodic characteristics. The dynamical characteristics are certified by the microcontroller execution of NSAGPMSM in the absence of external disturbances. By optimizing the parameters of NSAGPMSM in the absence of external disturbances, thanks to the convergence of the objective function and its convergence rate, it is proven that GAs is effective in optimizing system parameters, leading to annihilation of chaos in the system to one of its three steady states.