基于单神经元的参数自学习模糊控制器的研究  

Research of Parameter Self-learning Fuzzy Controller Based on Single Neuron

作　　者：张剑[1] 许镇琳[1] 王天将[1] 

机构地区：[1]天津大学,天津300072

出　　处：《中小型电机》2005年第2期18-21,共4页S&M Electric Machines

摘　　要：为进一步改善永磁交流伺服系统的动静态性能,本文设计了一种基于单神经元的参数自学习模糊控制器,它在控制规则数与二维控制器相当的基础上,可实现三维模糊控制的效果。引入的单神经元采用改进的BP算法来实现比例因子的在线自学习。控制器具有结构及算法简单、易于解析实现的特点。为验证其有效性,本文通过仿真试验,将其与采用常规的PI调节器的控制系统进行比较,结果表明,这种模糊控制器具有较好的控制效果。A parameter self-learning fuzzy controller based on single neuron is proposed. A three-dimensional fuzzy controller is implemented by simply using a two-dimensional fuzzy control rule-base without any increase of rules. The control parameters are self-tuned by introducing a single neuron together with a back-propagation learning algorithm. This method has simpler structure and control algorithms and can be realized online easily. Simulation results show that the performance is better than that of PI controller, and the system is much more robust.

关 键 词：单神经元 永磁交流伺服系统 自学习模糊控制器 PI调节器 静态性能 控制规则 比例因子 BP算法 仿真试验 控制系统 控制效果 器具 二维 在线 

分 类 号：TP273[自动化与计算机技术—检测技术与自动化装置] TS194.332[自动化与计算机技术—控制科学与工程]