仿生水下机器人的增强学习姿态镇定  

Reinforcement learning based attitude stabilization for bionic underwater robots

作　　者：林龙信[1] 谢海斌[2] 沈林成[2] 

机构地区：[1]海军装备研究院,北京100161 [2]国防科技大学机电工程与自动化学院,长沙410073

出　　处：《北京科技大学学报》2012年第1期76-79,共4页Journal of University of Science and Technology Beijing

基　　金：国防基础科研资助项目(D2820061301);国家自然科学基金资助项目(60805037)

摘　　要：针对一类双波动鳍仿生水下机器人的姿态镇定问题,提出一种基于增强学习的自适应PID控制方法.对增强学习自适应PID控制器进行了具体设计,包括PD控制律和基于增强学习的参数自适应方法.基于实际模型参数对偏航角镇定问题进行了仿真试验.结果表明,经过较小次数的学习控制后,仿生水下机器人的偏航角镇定性能得到明显改善,而且能够在短时间内对一般性扰动进行抑制,表现出了较好的适应性.A reinforcement learning based adaptive PID controller was presented for the attitude stabilization of a kind of bionic underwater robot with two bionic undulating fins. The scheme of the reinforcement learning based adaptive PID controller was given concretely including the control law and the parameter adaptive method based on reinforcement learning. Simulation experiments of yaw angle stabilization based on actual model parameters were carried out. The results indicate that the stabilization performance of yaw angle is improved distinctly after several iterations of learning control and the controller can overcome ordinary disturbances in short time, exhibiting its preferable adaptability.

关 键 词：机器人 仿生学 水下机器人 增强学习 自适应控制 姿态控制 

分 类 号：TP242[自动化与计算机技术—检测技术与自动化装置] TP181[自动化与计算机技术—控制科学与工程]