通用模型模糊神经网络控制  

Common Model Control Based on Fuzzy Neural Network

作　　者：樊四良[1] 郭丙君[1] 

机构地区：[1]华东理工大学信息科学与工程学院,上海200237

出　　处：《自动化仪表》2009年第12期58-60,64,共4页Process Automation Instrumentation

摘　　要：针对通用模型控制要求被控对象有显式解的局限性,提出一种基于模糊神经网络的通用模型控制方法。该方法是在控制算法中直接嵌入过程模型,从而保证了通用模型控制策略的可实现性。通用模型模糊神经网络控制与基于模糊逻辑的通用模型控制相比,其控制性能更好。仿真实验验证了该控制策略的有效性和鲁棒性。In order to overcome the limitation of common model control, i.e. explicit solution is requested tor controlled object, the memoo oi common model control based on fuzzy neural network is proposed. With the method, process model is directly embedded in control algorithm, thus the feasibility of implementing the control strategy is guaranteed. Comparing with the strategy based on fuzzy logic, the control performance is better. The simulated experiment verifies the effectiveness and robustness of the control strategy.

关 键 词：非线性 通用模型控制 模糊神经网络 逆控制 一般模型控制 模糊逻辑 

分 类 号：TP273.3[自动化与计算机技术—检测技术与自动化装置]