基于改进BFO优化的高速无人艇航向PD控制

PD Heading Control of High-speed USV Based on Improved BFO Optimization

针对无人艇高速航行过程中航向控制问题,提出一种基于改进细菌觅食算法优化的PD控制算法.基本细菌觅食算法使用固定步长易导致算法遗失局部最优解,文章设计了一种改进的分维自适应步长策略,以实现步长的自适应调整;针对细菌觅食算法的游动操作可能导致细菌重复的无用游动,提出了一种智能探针操作方法;引入一种自适应迁徙概率算法,优化细菌觅食算法的驱散操作;将改进后的细菌觅食算法融合到高速无人艇的PD航向控制系统当中,用于优化PD控制参数,并通过半物理仿真实验验证了所提出算法的有效性、可靠性和优越性.

Aiming at the heading control problem of Unmanned Surface Vessel(USV)during high-speed navigation,a PD control algorithm based on improved bacterial foraging algorithm optimization was proposed..As the basic bacterial foraging algorithm used a fixed step to lose the local optimal solution,an improved separated dimension adaptive step strategy was designed to realize the adaptive adjustment of the step in this paper.In view of the fact that the swimming operation of bacteria foraging algorithm may lead to repeated useless swimming of bacteria,an intelligent probe operation method was proposed.And an adaptive migration probability algorithm was introduced to optimize the dispersal operation of bacterial foraging algorithm.The improved bacterial foraging algorithm was integrated into the PD heading control system of high-speed USV to optimize PD control parameters,and the effectiveness,reliability and superiority of the proposed algorithm were verified by semi-physical simulation experiments.