High-Performance Model Predictive Control for Quadcopters with Formal Stability Guarantees

TL;DR

This paper introduces a high-performance model predictive control framework for quadcopters that guarantees formal stability and effectively tracks fast trajectories by integrating outer-loop MPC with an inner-loop nonlinear controller.

Contribution

It presents a novel cascade control architecture with formal stability guarantees and explicit thrust constraint handling, advancing quadcopter control methods.

Findings

Successfully tracks fast trajectories with small errors

Demonstrates stability and robustness through numerical case studies

Validates approach on high-fidelity models

Abstract

In this paper, we present a novel cascade control structure with formal guarantees of uniform almost global asymptotic stability for the state tracking error dynamics of a quadcopter. The proposed approach features a model predictive control strategy for the outer loop, explicitly accounting for the non-zero total thrust constraint. 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. The proposed cascade control strategy is validated through numerical case studies, underlying high-fidelity models, demonstrating its ability to track fast trajectories with small error.