L1-Adaptive MPPI Architecture for Robust and Agile Control of Multirotors

TL;DR

This paper introduces a combined control architecture using MPPI and L1 adaptive control to enhance the robustness and agility of multirotor vehicles, enabling real-time trajectory planning and robust tracking in complex environments.

Contribution

The paper proposes a novel integration of MPPI with L1 adaptive control, improving robustness of multirotor control systems against model uncertainties and dynamic variations.

Findings

Enhanced robustness in multirotor control demonstrated in simulations.

Successful real-time trajectory planning with MPPI in complex scenarios.

L1 adaptive control maintains trajectory tracking despite model discrepancies.

Abstract

This paper presents a multirotor control architecture, where Model Predictive Path Integral Control (MPPI) and L1 adaptive control are combined to achieve both fast model predictive trajectory planning and robust trajectory tracking. MPPI provides a framework to solve nonlinear MPC with complex cost functions in real-time. However, it often lacks robustness, especially when the simulated dynamics are different from the true dynamics. We show that the L1 adaptive controller robustifies the architecture, allowing the overall system to behave similar to the nominal system simulated with MPPI. The architecture is validated in a simulated multirotor racing environment.