# A Review of Control Algorithms for Autonomous Quadrotors

arXiv: https://arxiv.org/abs/1602.02622 · HTML: https://mlsanity.com/paper/1602.02622/

## Key facts

- Cited by 2 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 8 Feb 2016.

## Built on by (most cited first, 2 of 2)

- [A Reinforcement Learning Approach for Robust Supervisory Control of UAVs Under Disturbances](https://mlsanity.com/paper/2305.12543/) (2023)
- [Self-Tuning PID Control via a Hybrid Actor-Critic-Based Neural Structure for Quadcopter Control](https://mlsanity.com/paper/2307.01312/) (2023)

## Abstract (arXiv)

The quadrotor unmanned aerial vehicle is a great platform for control systems research as its nonlinear nature and under-actuated configuration make it ideal to synthesize and analyze control algorithms. After a brief explanation of the system, several algorithms have been analyzed including their advantages and disadvantages: PID, Linear Quadratic Regulator (LQR), Sliding mode, Backstepping, Feedback linearization, Adaptive, Robust, Optimal, L1, H-infinity, Fuzzy logic and Artificial neutral networks. The conclusion of this work is a proposal of hybrid systems to be considered as they combine advantages from more than one control philosophy.