AUV自主控制全局模型及智能决策算法研究

Research on AUV's Global Model for Autonomous Control and Algorithm of Intelligent Decision

分析了自主式水下潜器(AUV)自主控制全局模型的内涵,指出应该包含环境信息、使命信息以及自身状态三个部分;用栅格法建立了环境模型;定义了“多区域地形勘察”使命案例;分析了与决策算法相关的AUV自身状态的表示方法;在此基础上开发了智能决策算法,算法包含路径选优和速度规划两部分;应用图论及运筹学的方法实现了路径选优,应用遗传算法实现了速度规划;用Petri网为AUV的使命控制过程建模,最终完成了智能决策算法和使命控制系统的集成;经仿真验证,所开发的智能决策决策算法正确有效,AUV使命的控制和执行自主可靠。

The meaning of global model for AUV＇ s autonomous control is analysed, it should include 3 parts ： environment information, mission information and AUV＇ s states. The environment model is built by grid model. The ＂multi - area seabed survey＂ mission is defined. The expression method of AUV＇ s states which are correlative with decision algorithm is analysed. On the basis of the global model, the algorithm of intelligent decision is developed, which is made up of two parts ： path planning and velocity planning. The path planning is attained by using graph theory and operational research, and velocity planning is attained by using genetic algorithm. The mission control procedure is modeled by Petri net, and finally the intelligent algorithm is integrated into the mission control system. The simulation shows that the intelligent algorithm is valid and efficient, the control and execution of the mission are autonomous and reliable.