摘要
遗传算法优化函数参数可能会出现不足,为此采用高斯变异与柯西变异相结合的克隆算法,优化了变结构模糊神经网络的参数,并基于此方法设计控制器,应用于AGC控制系统。仿真实验结果表明,应用克隆算法比遗传算法优化参数收敛速度更快,用于AGC控制性能更好。
Owing to the insufficiency of genetic algorithm in optimizing of function parameters, this research is to design a controller for the control of AGC system based on clonal algorithm. The clonal algorithm combines the Gauss variation with the Cauchy variation to optimize the function parameters. The simulating results show that the clonal algorithm has higher speed of convergence than the genetic algorithm , Which enables it to be more effective for process control in AGC system.
出处
《钢铁研究》
CAS
2008年第4期37-40,共4页
Research on Iron and Steel
基金
国家自然基金项目(60573065)
关键词
遗传算法
克隆算法
高斯变异
柯西变异
AGC系统
genetic algorithm
clonal algorithm
Gauss variation
Cauchy variation
AGC system
