基于PPO算法的仿生鱼循迹智能控制

Intelligent Control of Bionic Fish Tracking Based on PPO Algorithm

仿生鱼具有广阔的工程应用前景,对于仿生鱼的控制,首先要解决的是循迹问题.然而,现有的基于CFD方式和传统控制算法的鱼游控制方法存在训练数据获取成本高、控制不稳定等缺点.本文提出了基于PPO算法的仿生鱼循迹智能控制方法:使用代理模型替代CFD方式产生训练数据,提高数据的产生效率;引入高效的PPO算法,加快策略模型的学习速度,提高训练数据的效用;引入速度参数,解决鱼体在急转弯区域无法顺利循迹的问题.实验表明,我们提出的方法在多种类型的路径上均具有更快的收敛速度和更加稳定的控制能力,在仿生机器鱼的智能控制方面具有重要的指导意义.

Bionic fish has broad prospect for engineering application.For the control of bionic fish,the first thing to solve is the tracking problem.However,the existing fish control methods based on CFD methods and traditional control algorithms feature high training data acquisition costs and unstable control.This study proposes an intelligent control method based on the PPO algorithm for bionic fish tracking.The surrogate model is employed instead of CFD to generate training data to improve the data generation efficiency.The efficient PPO algorithm is introduced to accelerate the learning speed of the strategy model and improve the utility of the training data.The speed parameter is introduced to solve the problem that the fish cannot track smoothly in the sharp turning area.Experiments show that the proposed method has faster convergence speed and more stable control ability in various paths,with guiding significance for the intelligent control of bionic robotic fish.