Emergent Mind

Abstract

In this paper, an adaptive super-twisting controller is designed for an agile maneuvering quadrotor unmanned aerial vehicle to achieve accurate trajectory tracking in the presence of external disturbances. A cascaded control architecture is designed to determine the desired accelerations using the proposed controller and subsequently used to compute the desired orientation and angular rates. The finite-time convergence of sliding functions and closed-loop system stability are analytically proven. Furthermore, the restrictive assumption on the maximum variation of the disturbance is relaxed by designing a gain adaptation law and low-pass filtering of the estimated equivalent control. The proper selection of design parameters is discussed in detail. Finally, the effectiveness of the proposed method is evaluated by high-fidelity software-in-the-loop simulations and validated by experimental studies.

We're not able to analyze this paper right now due to high demand.

Please check back later (sorry!).

Generate a summary of this paper on our Pro plan:

We ran into a problem analyzing this paper.

Newsletter

Get summaries of trending comp sci papers delivered straight to your inbox:

Unsubscribe anytime.