水下机器人S面控制器的免疫遗传算法优化

Immune-genetic optimization of underwater vehicle S surface controller

S面控制器是实践证明有效的水下机器人的运动控制器算法，但参数调整困难．如何针对特定载体选取最佳的控制器参数，是影响到控制效果的重要问题．为了减少参数手工调整所带来的误差和繁琐劳动，提出了水下机器人S面控制器的免疫遗传优化算法．利用免疫算法产生多样性抗体的能力，抗体浓度自我调节，抗原的免疫记忆功能实现了S面控制器参数优化计算的快速收敛，避免了局部峰值的徘徊．给出了S面控制器的推导过程，免疫遗传算法求解的一般过程．详细论述了S面控制器参数免疫遗传优化的具体实现．大量的仿真实验和湖中实验得到了确定性的结果．表明了此算法对于水下机器人运动非线性控制器的参数寻优能达到很好的效果．

S surface controller is proved to be effective in underwater vehicle motion control. But it is difficult to adjust parameters. It is a key problem how to choose optimum parameters of special underwater vehicle. To deduce error and fussy work of manual adjustment, immune-genetic optimization of underwater vehicle＇s S surface controller is proposed. The immune algorithm ability of producing various antibodies, antibody density self- adjustment, and antigen immune memory are used to realize rapid convergence of S surface controller parameters. It avoided loitering near local peak value. Deduction of S surface controller is given. General process of immune-genetic algorithm is described. Immune-genetic optimization of S surface controller parameters is discussed in details. Definitive results are gotten from many simulation experiments and lake experiments. The algorithm can get good effect in the parameter optimization of the underwater vehicle＇s nonlinear motion controller.