无人作业船自动导航控制系统的优化

Optimization of automatic navigation control system of unmanned working ship

为了提高原有导航系统中低成本传感器的数据检测精度和船体航迹跟踪的控制效果,引入数据融合算法并提出了一种新型的航迹跟踪算法.导航系统首先对船体进行多次坐标变换,通过两次卡尔曼滤波器融合出更精准的船体航向角、坐标和速度;其次提出了一种基于消除航迹速度偏差和航向角偏差的控制算法,将传统的PID控制器设计成由PI控制器和微分控制器组成的串级控制系统,作为内环的微分量正好由现有的加速度计和陀螺仪检测变送,省去了对微分参数的调节,对检测精度不高的系统也可以有较好的控制效果;最后解算出船体两个明轮各自需要的出力情况,以提高航迹跟踪效果.在试验平台上控制无人作业船进行多次巡航试验,通过上位机实时监测船体的状态数据和运行轨迹,并对整体优化后的航迹跟踪效果进行了分析.结果表明:经卡尔曼滤波器融合后的航向角、定位和速度,数据方差更小,更接近于理想值;对于控制算法,系统的超调量不超过3%,响应速度足够快,且稳态误差接近0;航迹跟踪的直线段成功率由优化前的80%提升到了95%,拐弯段的成功率由优化前的60%提升到了90%,直线段的最大偏航平均距离由优化前的0.83 m降到了0.12 m,拐弯段的最大偏航平均距离由优化前的1.25 m降到了0.22 m;拐弯后平均需要0.95 m长的调整距离就可以进入直行状态,直线段和拐弯段的跟踪效果明显得到了改善.

To improve the data detection accuracy of low-cost sensors in the original navigation system and the control effect of ship trajectory tracking,the data fusion algorithm was introduced to propose a new trajectory tracking algorithm.The multiple coordinate transformations of ship hull were conducted,and two Kalman filters were used to fuse more accurate ship heading angle,coordinates and velocity.The control algorithm based on eliminating trajectory velocity deviation and heading angle deviation was proposed.The traditional PID controller was designed as cascade control system with PI controller and differential controller.The differential variables in the inner loop were precisely detected and transmitted by the existing accelerometers and gyroscopes to eliminate the adjusting differential parameters for achieving good control results of systems with low detection accuracy.The each required output of the two vessels on the ship was calculated to improve the effect of trajectory tracking.The multiple cruise tests of unmanned working ship were conducted on the experimental platform with real-time monitoring the ship status data and operating trajectory through upper computer,and the overall optimized trajectory tracking effect was analyzed.The results show that the heading angle,positioning and velocity fused by the Kalman filter have smaller data variance and are closer to ideal values.For the control algorithm,the overshoot of the system does not exceed 3%,and the response speed is fast enough with the steady-state error of about zero.After optimization,the success rate of the straight section for trajectory tracking is increased from 80%to 95%,and the success rate of the turning section is increased from 60%to 90%.The maximum average yaw distance of the straight section after optimization is decreased from 0.83 m to 0.12 m,and the maximum average yaw distance of the turning section is decreased from 1.25 m to 0.22 m.After turning,the average adjustment distance of 0.95 meters is required to enter the straight state,and the tracking effects of straight and turning sections are significantly improved.