Coaxial Helicopter Attitude Control System Design by Advanced Model Predictive Control under Disturbance

This paper proposes an advanced model predictive control (MPC) scheme for the attitude tracking of coaxial drones under wind disturbances. Unlike most existing MPC setups, this scheme embeds steady-input, steady-output, and steady-state conditions into the optimization problem as decision variables. Consequently, the coaxial drone's attitude can slide along the state manifold composed of a series of steady states. This allows it to move toward the optimal reachable equilibrium. To address disturbances that are difficult to accurately measure, an extended state observer is employed to estimate the disturbances in the prediction model. This design ensures that the algorithm maintains recursive stability even in the presence of disturbances. Finally, numerical simulations and flight tests are provided to confirm the effectiveness of the proposed method through comparison with other control algorithms.