摘要
为了研究船舶可以从起始位置按预先规划好的航线准确且安全地自动抵达目的地的问题,本文提出了基于改进人工势场法的船舶路径规划与跟踪控制方法。采用模拟退火算法优化传统人工势场法的斥力函数,有效解决了传统人工势场法目标不可达和容易陷入局部极小值的缺陷。将规划的优化路径作为船舶运动控制系统的期望输入,基于内外环控制思想设计船舶运动学跟踪控制率,较好地解决了欠驱动船舶路径跟踪问题。在船舶动力学子系统中,利用神经网络逼近动力学子系统中的未建模动态及外部干扰,所设计的神经网络滑模跟踪控制器能够有效跟踪运动学子系统的引导率信号,同时解决了传统人工势场法在进行路径规划时不能统筹考虑外界通航环境干扰的缺陷。仿真实验验证了本文所提出的基于改进人工势场算法的船舶路径规划与跟踪控制的有效性。
To study the problem of ensuring that an underactuated surface vessel can arrive at its destination automatically, accurately, and safely from its starting position according to a pre-planned route, this paper presents a ship path planning and following control method based on improved artificial potential field method. The simulated annealing algorithm is used to optimize the repulsion function of the traditional artificial potential field method, which effectively solves the defects of the traditional artificial potential field method, such as unreachable target and the tendency to easily fall into local minimum value. The planned optimal path is taken as the expected input of the ship motion control system, and the control rate of ship kinematics tracking is designed based on the idea of inner and outer loop control, which are widely used in the industry. This approach better solves the problem of underactuated surface vessel path following. In a ship dynamic subsystem, with the use of the unmodeled dynamics and external disturbances of neural network approximation dynamic subsystem, the designed synovial tracking controller of the neural network can effectively track the boot rate signal of the kinematics subsystem and, at the same time, solve the traditional artificial potential field method for path planning without overall consideration of the defects of navigable environment disturbance. Simulation experiments verify the effectiveness of ship path planning and tracking control based on an improved artificial potential field algorithm.
作者
宁君
马昊冉
李铁山
NING Jun;MA Haoran;LI Tieshan(Navigation College,Dalian Maritime University,Dalian 116026,China;School of Automation Engineering,University of Electronic Science and Technology of China,Chengdu 611730,China)
出处
《哈尔滨工程大学学报》
EI
CAS
CSCD
北大核心
2022年第10期1414-1423,共10页
Journal of Harbin Engineering University
基金
国家自然科学基金重点项目(51939001)
国家自然科学基金项目(61976033,52171292,61803064)
中央高校基本科研业务费项目(3132022143)。
关键词
欠驱动船舶
路径规划
跟踪控制
模拟退火
改进人工势场算法
内外环控制
神经网络
滑模控制
underactuated surface vessel
path planning
tracking control
simulated annealing
improved artificial potential field algorithm
inner and outer ring control
neural network
sliding mode control
