Balancing a Flying Inverted Pendulum with an Unknown Length Using Model Predictive Control and a Genetic Algorithm Estimator

Abstract

This paper proposes an online Genetic Algorithm (GA) estimator and a Model Predictive Control (MPC) approach to solve the flying inverted pendulum problem in a practical experiment where the pendulum length is unknown. The performance of the MPC approach was demonstrated on a practical system through disturbance and trajectory tracking tests to assess controller robustness and tracking accuracy. The convergence speed and accuracy of the online GA estimator were validated on a practical system using different initial conditions.