论文标题

基于深钢筋学习的新型仿生形变尾巴的控制模式

A novel control mode of bionic morphing tail based on deep reinforcement learning

论文作者

Zheng, Liming, Zhou, Zhou, Sun, Pengbo, Zhang, Zhilin, Wang, Rui

论文摘要

在固定机翼飞机的田间,已经将许多变形技术应用于机翼,例如自适应机翼,可变跨度飞机,可变的扫掠角飞机等,但很少有人针对尾巴。传统的固定翼尾包括水平和垂直尾巴。受鸟尾巴的启发,该论文将引入新的仿生尾巴。尾部具有新型的控制模式,该模式具有多个控制变量。与传统的固定翼尾相比,它增加了纵向对称轴的区域控制和旋转控制,因此它可以同时控制飞机的俯仰和偏航。当尾部的区域变化时,可以更改飞机的可操作性和稳定性,并且飞机的空气动力学效率也可以提高。具有变形能力的飞机通常很难建立准确的数学模型,因为该模型具有强大的非线性,基于模型的控制方法很难处理强的非线性飞机。近年来,随着人工智能技术的快速发展,基于学习的控制方法也很出色,其中深度强化学习算法可以成为对控制对象的良好解决方案,这很难建立模型。在本文中,无模型控制算法PPO用于控制尾巴,并使用传统的PID来控制副翼和油门。在模拟中训练后,尾巴表现出出色的态度控制能力。

In the field of fixed wing aircraft, many morphing technologies have been applied to the wing, such as adaptive airfoil, variable span aircraft, variable swept angle aircraft, etc., but few are aimed at the tail. The traditional fixed wing tail includes horizontal and vertical tail. Inspired by the bird tail, this paper will introduce a new bionic tail. The tail has a novel control mode, which has multiple control variables. Compared with the traditional fixed wing tail, it adds the area control and rotation control around the longitudinal symmetry axis, so it can control the pitch and yaw of the aircraft at the same time. When the area of the tail changes, the maneuverability and stability of the aircraft can be changed, and the aerodynamic efficiency of the aircraft can also be improved. The aircraft with morphing ability is often difficult to establish accurate mathematical model, because the model has a strong nonlinear, model-based control method is difficult to deal with the strong nonlinear aircraft. In recent years, with the rapid development of artificial intelligence technology, learning based control methods are also brilliant, in which the deep reinforcement learning algorithm can be a good solution to the control object which is difficult to establish model. In this paper, the model-free control algorithm PPO is used to control the tail, and the traditional PID is used to control the aileron and throttle. After training in simulation, the tail shows excellent attitude control ability.

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