Recurrent Neural Network-Based Model Predictive Control for Multiple Unmanned Quadrotor Formation Flight
Autor: | Boyang Zhang, Xiuxia Sun, Shuguang Liu, Xiongfeng Deng |
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Jazyk: | angličtina |
Rok vydání: | 2019 |
Předmět: | |
Zdroj: | International Journal of Aerospace Engineering, Vol 2019 (2019) |
Druh dokumentu: | article |
ISSN: | 1687-5966 1687-5974 |
DOI: | 10.1155/2019/7272387 |
Popis: | This paper presents a dynamical recurrent neural network- (RNN-) based model predictive control (MPC) structure for the formation flight of multiple unmanned quadrotors. A distributed hierarchical control system with the translation subsystem and rotational subsystem is proposed to handle the formation-tracking problem for each quadrotor. The RNN-based MPC is proposed for each subsystem, where the RNN is introduced as the predictive model in MPC. And to improve the modeling accuracy, an adaptive updating law is developed to tune weights online for the RNN. Besides, the adaptive differential evolution (DE) algorithm is utilized to solve the optimization problem for MPC. Furthermore, the closed-loop stability is analyzed; meanwhile, the convergence of the DE algorithm is discussed as well. Finally, some simulation examples are provided to illustrate the validity of the proposed control structure. |
Databáze: | Directory of Open Access Journals |
Externí odkaz: | |
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