改进人工免疫算法在水下机器人运动控制中的应用研究

基于生物免疫系统的生理特性，以免疫系统T细胞、B细胞与免疫应答为基础，引入了免疫算法，其结构简单，易于实现，但是由于忽略了免疫系统的记忆、自适应、细胞繁殖和自然死亡等复杂的机理行为，也不具有实时自调整的能力。结合梯度搜索方法和希尔函数，提出了一种基于Sigmoid非线性模型的自学习免疫控制算法。将该方法应用于水下机器人的运动控制系统进行仿真研究，结果表明了改进人工免疫算法的有效性。

Improved immune control algorithm applied in motion control of autonomous underwater vehicle

Drawn lessons from the physiological character of creature immune system and normal immune control which based on the T cell,B cell and immunological response.The normal immune control could't self-learn in real time because it ignored the memory,adapt,cell replication and natural dead in immune system.It deduced a new self-learn immune control based on the Sigmoid non-linear model by gradient search method and hill function.The simulation results in autonomous underwater vehicle motion control can prove its efficiency.