A novel control mode of bionic morphing tail based on deep reinforcement learning
Liming Zheng, Zhou Zhou, Pengbo Sun, Zhilin Zhang, Rui Wang

TL;DR
This paper introduces a new bionic morphing tail for fixed wing aircraft, utilizing deep reinforcement learning to achieve effective control of pitch and yaw, enhancing maneuverability and stability.
Contribution
It proposes a novel control mode for a bionic tail with multiple control variables, employing PPO reinforcement learning for model-free control in aircraft.
Findings
The tail can control pitch and yaw simultaneously.
The reinforcement learning controller shows excellent attitude control after simulation training.
The morphing tail improves aircraft maneuverability and aerodynamic efficiency.
Abstract
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,…
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Taxonomy
TopicsBiomimetic flight and propulsion mechanisms · Aeroelasticity and Vibration Control · Adaptive Control of Nonlinear Systems
