High-performance model predictive control for quadcopters with time-varying constraints and formal stability guarantees

In this paper, we present a cascade control structure with formal stability guarantees for the state tracking error dynamics of a quadcopter. The proposed approach employs a novel model predictive control strategy in the outer loop that explicitly accounts for the nonzero total thrust constraint using time-varying input bounds. The outer-loop controller generates an acceleration reference, which is then converted into attitude, angular velocity and acceleration references, subsequently tracked by a nonlinear inner-loop controller. Uniform almost global asymptotic stability of the full cascade tracking error system, including continuous-time inter-sample behavior, is established. Numerical and high-fidelity case studies demonstrate that the proposed strategy substantially improves performance over existing stability-guaranteed MPC methods and achieves superior tracking performance compared to a baseline PID-based controller.