基于大脑情感学习的推力矢量无人机姿态控制

建立了与普通无人机相区别的带推力矢量的无人机数学模型，并提出了一种基于大脑情感学习(brain emotion learning, BEL)的推力矢量无人机姿态控制方法。首先设计了气动控制器和近似推力矢量控制器，然后设计了基于BEL算法的推力矢量控制补偿器。对无人机全量模型进行非线性数值仿真，结果验证了所建立的数学模型的正确性、推力矢量技术在无人机姿态控制上的特定优势以及BEL智能方法的自学习、自适应能力。

Attitude control of thrust vectoring unmanned aerial vehicle based on brain emotional learning

A mathematical model of a unmanned aerial vehicle with the thrust vectoring technology (UAV),which differs from the general model,is established.A new attitude control method of the UAV with the thrust vectoring technology based on a brain emotional learning (BEL) algorithm is presented.A pneumatic-rudder controller and a thrust vectoring controller are designed,respectively.Furthermore,a BEL algorithm based compensator of the thrust vectoring controller is derived.Nonlinear numerical simulation of a UAV whole model is implemented,the results show the correctness of the model,the particular advantages of the thrust vectoring technology in application of UAV attitude control and the self-learning adaptive ability of the BEL intelligent method.