摘要
针对神经控制器和遗传算法二者各自的优缺点,提出了遗传算法和神经控制的融合算法——将遗传算法应用于神经控制器的学习和训练,使控制器兼有二者的优点从而提高控制系统的性能。运用该方法对电加热炉温度控制系统进行的Matlab仿真,结果表明采用遗传神经控制器的系统,不但提高了阶跃响应的快速性,而且大大减少了超调量。
According to the advantages and defects of both genetic algorithm and neural controller, this paper brings forward a syncretic method of them--apply the genetic algorithm to the neural controller＇s learning and training. Thus the controller takes advantages of them to improve the capability of the control system. This method is used in an electric heater＇s temperature control system, and the results of Matlab simulation prove that the system of genetic-neural controller not only improves the speed of step response, but also greatly reduces the overstep quantity.
出处
《辽宁工程技术大学学报（自然科学版）》
CAS
北大核心
2006年第B06期178-180,共3页
Journal of Liaoning Technical University (Natural Science)
