Iterative learning-based formation control for multiple quadrotor unmanned aerial vehicles

Zhihui Zhao,Shuang Ju,Yangquan Chen,Jing Wang

doi:10.1177/1729881420911520

Abstract

A double-layer formation control is proposed to solve the repeated tasks for multiple quadrotor unmanned aerial vehicle systems. The first layer aims at achieving a formation target in which the iterative learning control is designed based on relative distance with neighbor unmanned aerial vehicles and absolute distance with virtual leader unmanned aerial vehicle. The formation controller is responsible for keeping the formation shape and generating the desired flying trajectories for each drones. The second layer control aims at achieving a high-precision tracking to desired flying trajectories which are generated from the formation controller. A double closed-loop proportional–derivative strategy is designed to ensure the accuracy of trajectory tracking for each individual drone. Simulations for the circle formation mission of the multiple quadrotor unmanned aerial vehicle system are given to verify the efficiency of the proposed method.

Highlights

The formation control of multiple quadrotor unmanned aerial vehicles (UAVs) is a central branch of research in recent years because of its potential applications in military, civilian, science, and technology.[1,2,3] In a formation control system, a group of UAVs are assembled to complete a task cooperatively, which is called as formation cooperation control.[4]
In the presence of external disturbances, a leader–follower formation control problem has been studied for multiple quadrotors UAVs.[12]
The objective considered in this article is to find an appropriate iterative learning control (ILC) algorithm to keep the formation shape and generate the desired trajectories for each quadrotor UAV in the formation system

Summary

Introduction

The formation control of multiple quadrotor unmanned aerial vehicles (UAVs) is a central branch of research in recent years because of its potential applications in military, civilian, science, and technology.[1,2,3] In a formation control system, a group of UAVs are assembled to complete a task cooperatively, which is called as formation cooperation control.[4]. An ILC algorithm based on leader–follower formation tracking problem has been presented for a multi-agent system.[23] An ILC algorithm has been studied for all agents who track a time-varying desired trajectory in a directed graph.[24] in most of the above-cited literature, the formation system requires that each drone should be controlled by the same control method, thereby limiting the diversity of the system. An ILC-based formation control problem is studied to track a time-varying reference trajectory in a directed graph for the multiple quadrotor UAV system. The second control layer which is called inner-loop layer contains a double closed-loop PD controller for the trajectory tracking of the individual quadrotor UAV. A double closed-loop PD controller is designed to keep every drone tracking its trajectory. The rotation matrixes are REBðÞ 1⁄4 664 0 cos Àsin 775

Àsin q 0 cos q 3 cos Àsin 0

Conclusions