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.
出处
《自动化仪表》
CAS
北大核心
2009年第12期58-60,64,共4页
Process Automation Instrumentation
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
Non-linearity Common model control Fuzzy neural network Inverted control General model control Fuzzy logic
