基于RBF神经网络补偿的动力定位PD控制

动力定位控制系统在实际工况中会受到外部风、浪、流等环境力的扰动,本文主要研究PD+RBF控制算法以提高动力定位系统的抗干扰性和稳定性.RBF神经网络用来补偿外界环境扰动,其权值自适应律通过Lyapunov稳定性证明得到,通过稳定性的分析能够保证整个系统全局渐进稳定.在一艘平台供应船的仿真结果对比中显示了所提出控制器的有效性.

PD Control with RBF Neural Network Compensation for Dynamic Positioning System

Dynamic positioning control system is influenced inevitably by external environment distur-bances such as wind, wave and current in actual working conditions. This paper mainly studies the RBF neural network and PD control algorithm to improve the immunity and stability of a dynamic posi-tioning system. RBF neural network is used to compensate for the environment disturbances, whose adaptability and robustness can be enhanced. The adaptive algorithm of weights is obtained by Lyapu-nov function analysis. Simulation comparison results of a supply ship confirm the effectiveness of the proposed controller.