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Affine Formation Control of Multiple Quadcopters | IEEE Conference Publication | IEEE Xplore

Affine Formation Control of Multiple Quadcopters


Abstract:

This paper considers the distributed time-varying formation tracking control problem of multi-quadcopter systems using affine formation control strategies with multiple v...Show More

Abstract:

This paper considers the distributed time-varying formation tracking control problem of multi-quadcopter systems using affine formation control strategies with multiple virtual leaders. A novel two-layer (formation layer and local control layer) affine formation control structure is established to account for the underactuated nature of the quadcopter dynamics. In the formation layer, a quadcopter is abstracted as a virtual double-integrator agent and affine formation controllers are then designed based on the networked double-integrator dynamics. The resultant virtual affine formation control inputs from the formation layer are converted to the desired attitudes based on the quadcopter dynamics, and a sliding mode controller is then proposed to ensure flnite-time tracking convergence to the desired attitude in the local control layer. Numerical simulations were carried out using a group of six quadcopters in the XY-plane to demonstrate and validate the effectiveness of the developed controllers.
Date of Conference: 17-20 October 2022
Date Added to IEEE Xplore: 09 December 2022
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ISSN Information:

Conference Location: Brussels, Belgium

I. Introduction

Quadcopters are mechanically simple, highly maneuverable and capable of vertically taking off and landing. In recent years, multiple-quadcopter systems have been applied in various fields to accomplish tasks, such as forest fire monitoring and load transportation, that would be impossible or inefficient for a single qaudcopter system. Formation control design, where the entire group is driven to achieve and maintain a certain geometric pattern, is often required to enable these applications. Although some formation control approaches, such as virtual structure and behavior-based, are effective and easy to implement for many systems with complex dynamics, the overall system stability analysis is mathematically challenging and the convergence is often not guaranteed. Recently, the consensus-based [1] formation control methods that can guarantee the overall system convergence have prevailed.

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References

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