一种无人船动力定位跨平台实时控制模型

为了更好地将实时控制算法应用于无人船的自动导航,针对以往跨平台实时控制的数据类型不统一、通信不可靠等问题,根据日本国立水产工学研究所进行无人船水池实验的研究模式,建立一种基于用户数据报协议(UDP)的远程控制模型,该模型在服务器端使用python编写,在客户端使用Matlab/Simulink.为验证控制的实时性,在实验水池进行基于自抗扰控制技术的航向控制实船实验,同时验证所设计控制系统的实时性和控制算法的有效性.在系统测试时,采用基于RBF神经网络抗扰算法对无人船动力定位系统进行仿真,并对所设计的控制器进行稳定性分析.仿真实验结果表明,应用不同编程环境进行复杂远程控制UDP通信是平稳的,过程控制结果令人满意,为后续进行复杂无人船实船实验奠定了基础.

Real-time cross-platform control system for unmanned ship dynamic positioning

In order to better apply the real-time control algorithm to the automatic navigation of unmanned ships, a remote control system based on user datagram protocol(UDP) is established according to the Japanese national research institute of fisheries engineering (NRIFE), the system uses python on the server side and Matalb/Simulink on the client side. Aiming at the problems of inconsistent data types and unreliable communication of cross-platform real-time control in the past, specific solutions are proposed. In order to verify the real-time performance of the control, a real-time course control experiment based on the active disturbance rejection control (ADRC) technology is carried out in the experimental tank, which verifies the real-time performance of the designed control system and the effectiveness of the control algorithm. When testing the system, the simulation of the unmanned ship dynamic positioning system is carried out using the RBF neural network disturbance rejection algorithm, and the stability of the controller is analyzed. The experimental results show that the UDP communication of remote control is smooth and the control results are satisfactory, which provides the foundation for subsequent complex unmanned ship experiments.