一种新的复杂系统模糊辨识方法
A New Fuzzy Identification Method for Complex Systems
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摘要: 针对一阶Takagi-Sugeno模型辨识复杂系统的困难,提出一种新的模糊模型.这种模 型的结构在一阶Takagi-Sugeno模型的基础上,再进行一次非线性映射.文中运用卡尔曼滤 波算法的模糊神经元网络实现了这种模型.仿真结果表明该方法辨识精度高,且有良好的 实用性.Abstract: In this paper, a new fuzzy model is presented to overcome the difficulty of using the first order Takagi-Sugeno model to identify complex systems. The structure of the new model is based on the first order Takagi-Sugeno model, but a nonlinear mapping is added to. In order to realize the model, a fuzzy neural network (FNN) with Kalman filter algorithm is then implemented. Simulation results show that this method is very efficient and practical.
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Key words:
- Fuzzy identification /
- fuzzy neural network /
- system identification
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