深海自行式集矿机的定位与综合导航

Positioning and Composed Navigation for Self-propelled Collector in Deep-sea Mining

应用模糊自适应扩展卡尔曼滤波方法,研究了深海采矿集矿机的定位导航问题。建立了履带式集矿机的状态空间模型,根据长基线定位系统的延时建立了系统的测量方程,提出了基于模糊逻辑的自适应卡尔曼滤波的算法。仿真结果表明:集矿机位置X,Y的新息系列均在±σ的范围内变化,采用该自适应控制算法对Q、R加权的方法所进行的卡尔曼滤波是稳定的、最优的。

The fuzzy adaptive EKF （Extensive Kalman Filter） was used to predict the position estimation and navigation for deep - sea collector. The state space model of the crawler type collector was constructed and the measurement equation of the LBL （ long base line） system was presented according to the latency of the system. The logical algorithms based on the fuzzy adaptive EKF were put forward. The simulation results show that the innovation series of the position X and Y of the collector are within the ±σ limits, and the estimates produced by the adaptive EKF using adaptive algorithms to weight R and Q are stable and optimal.