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

作者：Qingqing Zheng, Renjie Tang, Siyuan Gou, Zhang Weizhong · 年份：2020 · DOI：10.23919/ccc50068.2020.9188426 · 被引用次数：9 · 研究领域：Adaptive Control of Nonlinear Systems、Adaptive Dynamic Programming Control、Extremum Seeking Control Systems

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.