船舶拟人智能避碰决策方法研究综述

回顾我校研发团队20年来在船舶自动避碰技术的研究历程,简要介绍了船舶拟人智能避碰决策（PIDVCA）方法,重点论述了《机器决策》的“拟人智能”特性,并借助船舶智能操控（SIHC）仿真平台,通过设计典型会遇态势加以验证。研究结果表明：基于PIDVCA方法的《机器决策》可以同时安全避让2～4个危险目标船,达到了预期的研究目标,最后指出PIDVCA方法尚存的问题及日后研究方向。     

基于“新大纲”的“航海仪器的正确使用”课程改革与实践

在深入研究STCW公约及《中华人民共和国海船船员适任评估大纲和规范》的基础上,针对当前“航海仪器的正确使用”适任评估存在的问题,结合实际设计出适用于新大纲评估训练的课时安排、实操训练方案和评估考试方法。     

Robust Fuzzy Sampled-Data Control for Dynamic Positioning Ships

A robust H∞sampled-data stabilization problem for nonlinear dynamic positioning(DP) ships with Takagi-Sugeno(T-S) fuzzy models is discussed in this paper. Input delay approach is used to convert the sampleddata DP ship system to a fuzzy system with time-varying delay. Adequate conditions are derived to determine the system's asymptotical stability and achieve H∞performance via Lyapunov stability theorems. Then, the fuzzy sampled-data controller is obtained by analyzing the stabilization condition. Simulation result shows that the proposed method and the designed controller for a DP ship are effective so that the DP ship can maintain the desired position, heading and velocities in the existence of varying environment disturbances.