摘要
基于遗传算法与免疫系统的机理,提出了一种自适应免疫遗传算法(AIGA).该算法定义了选择、扩展与突变等操作,通过对选择比例、扩展半径、突变半径的约束和参数的自适应调节,提高了算法的全局与局部搜索能力.同时,将AIGA用于系统辨识以及PID参数的优化中,进行了仿真实验,取得了较好的结果,证明了该方法的有效性.
An adaptive immune genetic algorithm （AIGA） was proposed on the basis of genetic algorithm and immune principle. The operation of selection, expansion, and mutation was defined first for this algorithm, and its global and local searching ability was improved by means of constraining three new parameters such as selection scale, expansion radius, and mutation radius and adaptively adjusting them. A simulation test of system identification and PID parameter optimization was conducted with ALGA. A good result was obtained, so that the feasibility of this method was confirmed.
出处
《兰州理工大学学报》
CAS
北大核心
2006年第3期85-88,共4页
Journal of Lanzhou University of Technology
基金
国家重大科技攻关项目(2002BA901A28)
甘肃省省长基金(GS015-A52-012)
