论文部分内容阅读
针对未知环境下多无人机(UAV)分布式协同搜索问题,对分布式搜索的通信交互和决策最优性进行了分析,给出了分布式纳什均衡解的求解方法.在分布式控制框架下,建立了基于滚动优化的多机搜索的问题描述和状态空间模型,并针对传统协同收益指标的不足,提出了基于人工势场的协同收益模型,与模糊控制相结合,建立模糊规则求解协同收益,增加了决策的鲁棒性.仿真实验验证了提出的协同搜索方法的有效性.
Aiming at the problem of UAV distributed collaborative search in unknown environment, the communication interaction and decision optimality of distributed search are analyzed, and the solution method of distributed Nash equilibrium solution is given.In the distributed control framework , The problem description and state space model of multi-machine search based on rolling optimization are established. In order to overcome the shortcomings of the traditional index, a collaborative revenue model based on artificial potential field is proposed, which is combined with fuzzy control to establish fuzzy rules to solve the problem And enhances the robustness of decision making.The simulation results show the effectiveness of the proposed collaborative search method.