EMPC-Based Flight Control and Collision-Free Path Planning for a Quadrotor With Unbalanced Payload

In this article, a robust explicit model predictive control (EMPC) flight scheme is investigated for a quadrotor. MPC is widely recognized for its control effectiveness, but the computational complexity involved in solving online optimization problems, particularly when applied to fast systems, poses a significant challenge. To enable real-time MPC implementation on quadrotor systems, we propose a novel dual-layer control architecture integrating EMPC, strategically relocating the computationally intensive optimization process to offline computation. The outer loop computes reference roll and pitch angles, while the inner loop employs an EMPC framework to achieve fast attitude tracking considering state and actuator constraints. Moreover, integral sliding mode control (ISMC) is integrated to mitigate the effects of uncertainties, such as unbalanced payloads. The recursive feasibility is guaranteed for the proposed flight control method if the initial states are in the feasibility set, and the Lyapunov stability analysis is conducted. In addition, we develop a polynomial trajectory planning algorithm for the quadrotor in (3-D) space. We employ our previous result, the bidirectional guidance informed trees (BIGIT*) algorithm, to obtain a sequence of collision-free waypoints, and utilize the minimum-snap technique to generate a smooth path. Finally, experimental results demonstrate the effectiveness of the proposed methods.