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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.
Aiming at the problem of attitude stabilization for a class of bifurcated fin biomimetic underwater robots, an adaptive PID control method based on enhanced learning is proposed. The adaptive learning PID controller is designed specifically, including PD control law and enhanced learning The parameter adaptive method is used to simulate the yaw angle stabilization problem based on the actual model parameters.The results show that after a small number of learning control, the yaw angle stabilization performance of the bionic underwater robot can be significantly improved, Time to suppress the general disturbance, showed a good adaptability.