Selective robust control improves quadrotor flying in wind and load
Selective Sliding Mode Control Enhances Robustness of Aerial Robots Under Disturbances
Robotics
Summary
Flying small drones like quadrotors can be tricky when there’s wind or they’re carrying heavy stuff. The authors show that not all parts of the drone’s control system need extra protection against disturbances—only certain parts really benefit. They figured out how to spot exactly which parts to make stronger by analyzing the drone’s movements during flight. Testing on a real quadrotor showed better flying accuracy on these chosen parts without wasting effort on others.
What this means in practice
- •For drone engineers: Improve quadrotor flight stability by applying robust control selectively to affected axes under wind or payload disturbances.
- •For embedded control developers: Reduce computational load by tuning robust control loops only where disturbances act on quadrotor control systems.
Authors
Anoop Kiran, Thales C. Silva, Nora Ayanian
Abstract
Quadrotor control under disturbances such as wind gusts and payload variations remains challenging. First-order sliding mode control (SMC) and matched/unmatched uncertainty distinction are classical approaches; however, neither tells a practitioner which loops in a cascaded controller should be made robust to sustain disturbances, how to tune those loops, nor what the additional costs are on an embedded processor. Applying robust control uniformly across all axes addresses disturbances indiscriminately, adding tuning effort on axes where no disturbance acts. On inherently underactuated vehicles, disturbances along some axes cannot be opposed directly at all. We propose a principled methodology for deciding where robust control belongs in a cascaded architecture, with all control running onboard the vehicle. We recover the acting disturbance from PID hover flights under disturbance by inverting the equations of motion, use the recovered signal to identify and quantify the excited axes, and deploy robust control where it counts. Experiments on a Crazyflie 2.1 quadrotor under slung-payload and oblique-wind disturbances show tracking improvements concentrated on the axes the rule selects, and gain sweeps confirm that the switching gain reduces error on matched axes but has no effect on an excited unmatched axis, as the analysis predicts.