哈尔滨工程大学学报2024，Vol.45Issue(1)：198-203,6.DOI:10.11990/jheu.202202010
基于事件触发机制的动力定位系统神经自适应控制
Neural adaptive control of a dynamic positioning system based on an event-triggered mechanism
摘要
Abstract
This paper proposes a neural adaptive control algorithm based on an event-triggered mechanism for sol-ving the dynamic positioning control of surface vessels with model parameter uncertainties and environmental dis-turbances.First,an adaptive item is designed to compensate for the environmental disturbances and model parame-ter uncertainties by using the radial basis function neural network and the minimum learning parameter algorithm.The designed adaptive item has only three online learning parameters,thereby reducing the number of learning pa-rameters of the traditional neural network adaptive methods.A dynamic positioning controller is designed by combi-ning the dynamic surface control technology and an event-triggering mechanism,wherein the latter is introduced to reduce the load of information communication from the controller to the actuator and concurrently lower the execu-tion rate of the actuators.Then,the stability of the closed-loop system is analyzed using the Lyapunov theory.Finally,the effectiveness of the proposed control law is verified through simulation and comparative analysis.关键词
动力定位系统/动态面控制/事件触发机制/最小学习参数/神经网络Key words
dynamic positioning system/dynamic surface control/event-triggered mechanism/minimum learning parameter/neural network分类
信息技术与安全科学引用本文复制引用
孙创,覃月明,夏天,夏国清..基于事件触发机制的动力定位系统神经自适应控制[J].哈尔滨工程大学学报,2024,45(1):198-203,6.基金项目
工业和信息化部高技术船舶重大创新专项 （）
中国船舶重工集团有限公司2018年度科技创新与研发项目(201808K). （201808K）
