基于多策略免疫遗传算法的无人艇航向自适应控制

Adaptive control method of unmanned surface vehicle course based on MSFIGA algorithm

针对无人艇在真实水面环境下的航向跟踪控制问题,提出一种基于多策略融合改进免疫遗传算法(MSFI⁃GA)的无人艇航向自适应控制方法。首先,建立无人艇的二阶非线性运动模型和环境风浪流干扰模型。其次,提出一种基于多策略融合改进的免疫遗传算法,通过引入混沌初始化、向量角相似度及自适应差分接种等策略,改善基本算法收敛缓慢、易陷入局部最优的缺点;在此基础上,设计基于MSFIGA的无人艇航向自适应控制器及性能评价函数,以实现对无人艇控制参数的自适应优化。最后,通过对比仿真试验和在线仿真试验验证该方法的优越性和实用性。

Aiming at the problem of course tracking control of unmanned surface vehicles in real water environment,an adaptive course controller of unmanned boats based on multi-strategy fusion improved immune genetic algorithm(MSFIGA)was proposed.Firstly,the second-order nonlinear motion model of an unmanned vehicle and an environmental disturbance model of wind,wave and current were first established.Secondly,an improved immune genetic algorithm based on multi-strategy fusion was proposed.By introducing strategies such as chaotic initialization,vector angle similarity and adaptive differential vaccination,the shortcomings like converging slowly and falling easily into local optimum of the basic algorithm were well made up.On this basis,an adaptive course controller based on MSFIGA and performance evaluation function were designed to realize the adaptive optimization of the control parameters of the unmanned surface vehicle.Finally,the superiority and practicability of the method were verified by comparing the simulation test and the online simulation test.