Chaotic biogeography-based optimization approach to receding horizon control for multiple UAVs formation flight

Weiren Zhu; Haibin Duan

doi:10.1016/j.ifacol.2015.06.460

Chaotic biogeography-based optimization approach to receding horizon control for multiple UAVs formation flight

Weiren Zhu
, Haibin Duan

School of Automation Science and Electrical Engineering

Beihang University

Research output: Contribution to journal › Conference article › peer-review

7 Scopus citations

Abstract

In this paper, we proposed a Receding Horizon Control (RHC) scheme which converts multiple Unmanned Aerial Vehicle (UAVs) formation flight problem to a sequence of online optimization problems over a planning horizon. A novel Chaotic Biogeography-Based Optimization (CBBO) approach is presented to find the optimal control inputs for the follower UAVs to maintain coordinated flight with the minimum input cost in each of the planning horizons. Series of simulation results verified the feasibility and effectiveness of our presented approach.

Original language	English
Pages (from-to)	35-40
Number of pages	6
Journal	IFAC-PapersOnLine
Volume	28
Issue number	5
DOIs	https://doi.org/10.1016/j.ifacol.2015.06.460
State	Published - 1 May 2015
Event	3rd IFAC Workshop on Multivehicle Systems, MVS 2015 - Genova, Italy Duration: 18 May 2015 → …

Keywords

Biogeography-Based Optimization (BBO)
Formation Flight
Unmanned Aerial Vehicles (UAVs)

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10.1016/j.ifacol.2015.06.460

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title = "Chaotic biogeography-based optimization approach to receding horizon control for multiple UAVs formation flight",

abstract = "In this paper, we proposed a Receding Horizon Control (RHC) scheme which converts multiple Unmanned Aerial Vehicle (UAVs) formation flight problem to a sequence of online optimization problems over a planning horizon. A novel Chaotic Biogeography-Based Optimization (CBBO) approach is presented to find the optimal control inputs for the follower UAVs to maintain coordinated flight with the minimum input cost in each of the planning horizons. Series of simulation results verified the feasibility and effectiveness of our presented approach.",

keywords = "Biogeography-Based Optimization (BBO), Formation Flight, Unmanned Aerial Vehicles (UAVs)",

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AU - Duan, Haibin

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N2 - In this paper, we proposed a Receding Horizon Control (RHC) scheme which converts multiple Unmanned Aerial Vehicle (UAVs) formation flight problem to a sequence of online optimization problems over a planning horizon. A novel Chaotic Biogeography-Based Optimization (CBBO) approach is presented to find the optimal control inputs for the follower UAVs to maintain coordinated flight with the minimum input cost in each of the planning horizons. Series of simulation results verified the feasibility and effectiveness of our presented approach.

AB - In this paper, we proposed a Receding Horizon Control (RHC) scheme which converts multiple Unmanned Aerial Vehicle (UAVs) formation flight problem to a sequence of online optimization problems over a planning horizon. A novel Chaotic Biogeography-Based Optimization (CBBO) approach is presented to find the optimal control inputs for the follower UAVs to maintain coordinated flight with the minimum input cost in each of the planning horizons. Series of simulation results verified the feasibility and effectiveness of our presented approach.

KW - Biogeography-Based Optimization (BBO)

KW - Formation Flight

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Chaotic biogeography-based optimization approach to receding horizon control for multiple UAVs formation flight

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