基于优化模糊神经网络控制的加热炉应用  

Application of heating furnace based on optimization fuzzy neural-network control

作　　者：詹习生[1] 张先鹤[1] 吴杰[1] 

机构地区：[1]湖北师范学院控制科学与工程系,湖北黄石435002

出　　处：《河北工业科技》2009年第5期331-334,共4页Hebei Journal of Industrial Science and Technology

摘　　要：针对加热炉具有大惯性和纯滞后性,提出优化模糊神经网络控制。该控制将模糊逻辑推理与神经网络控制技术融合,同时利用遗传算法优化隶属度函数,采用误差反向传播学习算法在线调节神经网络权值,提高了控制器的稳定性、鲁棒性和适应性。仿真结果证实了控制器的有效性。An optimization fuzzy neural network controller （FNNC） was proposed for heating furnace with great inertia and large time delay. The control method combined fuzzy control and neural network techniques, and at the same time genetic algorithm （GA） was applied to optimize the membership function. In addition, back propagation （BP） algorithm was adopted for on-line adjusting the weight values of the controller. Such issues as stability, adaptability and robustness in the controller were considered. Simulation result proves the effectiveness of the proposed controller.

关 键 词：模糊控制 神经网络 优化 加热炉 

分 类 号：TP273[自动化与计算机技术—检测技术与自动化装置]