A PID Gain Adjustment Scheme Based on Reinforcement Learning Algorithm for a Quadrotor

被引：0

作者：

Zheng Qingqing ^{[1
]}

Tang Renjie ^{[1
]}

Gou Siyuan ^{[1
]}

Zhang Weizhong ^{[1
]}

机构：

[1] Beijing Inst Technol, Sch Aerosp Engn, Beijing 100081, Peoples R China

来源：

PROCEEDINGS OF THE 39TH CHINESE CONTROL CONFERENCE | 2020年

关键词：

Quadrotor Control; PID controller; Reinforcement learning; PPO algorithm;

D O I：

暂无

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

In this paper, a PID gain adjustment scheme with the basis on Reinforcement Learning Algorithm is proposed, the validity of the scheme is demonstrated with the application to the control of a quadrotor. Specifically, the PPO algorithm of reinforcement learning is utilized in the scheme to adjust a PID controller gains. The procedure and details of the scheme are presented. The experiments prove that the control strategy with this scheme can quickly make the controlled system converge and stabilize. The scheme, compared with a traditional PID controller, has a good performance in terms of control stability, anti-interference stability, and aircraft altitude stability.

引用

页码：6756 / 6761

页数：6