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

arXiv: https://arxiv.org/abs/2004.00152 · HTML: https://mlsanity.com/paper/2004.00152/

## Key facts

- Cited by 14 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 31 Mar 2020.

## Built on by (most cited first, 14 of 14)

- [Neural-Fly Enables Rapid Learning for Agile Flight in Strong Winds](https://mlsanity.com/paper/2205.06908/) (2022)
- [Learning a Single Near-hover Position Controller for Vastly Different Quadcopters](https://mlsanity.com/paper/2209.09232/) (2022)
- [DATT: Deep Adaptive Trajectory Tracking for Quadrotor Control](https://mlsanity.com/paper/2310.09053/) (2023)
- [Active Learning of Discrete-Time Dynamics for Uncertainty-Aware Model Predictive Control](https://mlsanity.com/paper/2210.12583/) (2022)
- [Deep Model Predictive Optimization](https://mlsanity.com/paper/2310.04590/) (2023)
- [CoVO-MPC: Theoretical Analysis of Sampling-based MPC and Optimal Covariance Design](https://mlsanity.com/paper/2401.07369/) (2024)
- [Bayesian Optimisation for Robust Model Predictive Control under Model Parameter Uncertainty](https://mlsanity.com/paper/2203.00551/) (2022)
- [Neural Internal Model Control: Learning a Robust Control Policy via Predictive Error Feedback](https://mlsanity.com/paper/2411.13079/) (2024)
- [Robust Model Based Reinforcement Learning Using L1 Adaptive Control](https://mlsanity.com/paper/2403.14860/) (2024)
- [Safe Beyond the Horizon: Efficient Sampling-based MPC with Neural Control Barrier Functions](https://mlsanity.com/paper/2502.15006/) (2025)
- [Safety-Aware Imitation Learning via MPC-Guided Disturbance Injection](https://mlsanity.com/paper/2508.03129/) (2025)
- [Robustifying Reinforcement Learning Policies with L1 Adaptive Control](https://mlsanity.com/paper/2106.02249/) (2021)
- [Efficient Deep Learning of Robust, Adaptive Policies using Tube MPC-Guided Data Augmentation](https://mlsanity.com/paper/2303.15688/) (2023)
- [A Robust Task-Level Control Architecture for Learned Dynamical Systems](https://mlsanity.com/paper/2511.09790/) (2025)

## Abstract (arXiv)

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.