基于动态BP神经网络PID的AUV自适应控制

AUV Adpative Control Based on Dynamic BP Neural Network PID

由于自治水下机器人(AUV)动力学的非线性、模型参数以及海洋环境扰动的不确定性,基于常规PID控制的AUV性能通常不够理想。文中应用动态BP神经网络对PID控制器的参数进行在线调整,从而使PID控制器具有自适应性以适应AUV工况的变化,仿真结果验证了本策略的有效性。

The complexity of sea environment and the uncertainty of AUV model to difficulties of AUV control. The tradition PID controller of the AUV performance is not well. In this paper, the dynamic BP neural network PID controller parameters on-line adjustments, so that the adaptive PID controller has to adapt to changes in working conditions AUV simulation results validate the effectiveness of this strategy.