A model predictive control-based architecture for cooperative path-following of multiple unmanned aerial vehicles

• Type: Chapter or Part of a Book
• Date: 2015

Authors

Rucco, A (Author) Other; Aguiar, AP (Author) FEUP; fontes, facc (Author) FEUP; Fernando Lobo Pereira (Author) FEUP; João Tasso Sousa (Author) FEUP

Book

Title: Developments in Model-Based Optimization and Control. Distributed control and industrial applications

1º Edition

Pages: 141-160

ISBN: 978-3-319-26685-5

Electronic ISBN: 978-3-319-26687-9

Publisher: Springer Publishing

Indexing

Scopus - 13 Citations

Other information

Authenticus ID: P-00K-46A

DOI: 10.1007/978-3-319-26687-9_7

Abstract (EN): This chapter proposes a sampled-data model predictive control (MPC) architecture to solve the decentralized cooperative path-following (CPF) problem of multiple unmanned aerial vehicles (UAVs). In the cooperative path-following proposed scenario, which builds on previous work on CPF, multiple vehicles are required to follow pre-specified paths at nominal speed profiles (that may be path dependent) while keeping a desired, possibly time-varying, geometric formation pattern. In the proposed framework, we exploit the potential of optimization-based control strategies with significant advantages on explicitly addressing input and state constraints and on the ability to allow the minimization ofmeaningful cost functions. An example consisting of three fixed wing UAVs that are required to follow a given desired maneuver illustrates the proposed framework.We highlight and discuss some features of the UAVs trajectories. © Springer International Publishing Switzerland 2015.

Language: English

Type (Professor's evaluation): Scientific