Robust Predictive Functional Control for Quadrotor Flight Systems

Predictive Functional Control (PFC) has a control structure similar to Model Predictive Control (MPC), determining control inputs by predicting future states using a motion model. However, PFC does not require solving a quadratic programming problem for every control loop like MPC. This feature enables PFC to be implemented in small-scale systems such as actuators, where embedding a high-performance computer is difficult. However, similar to MPC, there are concerns with PFC regarding control performance degradation due to incorrect predictions of future states in environments affected by modeling errors and disturbances. Therefore, in this study, we propose a novel method that employs robustness, Robust Predictive Functional Control (RPFC). The proposed RPFC method was applied to a quadrotor flight control system, and its effectiveness was verified through numerical simulations. Specifically, the control performance of RPFC under disturbance conditions was compared with that of conventional PFC, demonstrating the advantages of the proposed approach.