Abstract
Formation flight has long been performed by many species of birds for its social and aerodynamic benefits. As a challenging interdisciplinary research topic, autonomous formation flight for multiple unmanned aerial vehicles (UAVs) is about flying in formations with precisely defined geometries, with the benefits of fuel saving and improved efficiency in air traffic control and cooperative task allocation. This chapter mainly focuses on three important aspects associated with formation, which are respectively formation control, close formation (tight formation), and formation configuration. A chaotic particle swarm optimization (PSO)-based nonlinear dual-mode receding horizon control (RHC) method is proposed to cope with the complexity and nonlinearity of vehicle dynamics. Then a novel type of control strategy of using hybrid RHC and differential evolution (DE) algorithm is proposed based on the nonlinear model of multiple UAV close formation. Moreover, based on the Markov chain model, the convergence of DE is proved. Finally, the formation configuration, which is about diving multiple UAVs to form a new flying formation state, is explained in detail using the RHC-based DE. The global control problem of multiple UAV formation reconfiguration is transformed into several online local optimization problems at a series of receding horizons, while the DE algorithm is adopted to optimize control sequences at each receding horizon.
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Duan, H. (2014). Multiple UAV Formation Control. In: Bio-inspired Computation in Unmanned Aerial Vehicles. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-41196-0_5
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DOI: https://doi.org/10.1007/978-3-642-41196-0_5
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