多变量自适应模糊控制器的设计
首发时间:2013-12-05
摘要:本文研究了一种多变量自适应模糊控制器的设计方法,采用单层神经网络来学习、建立并修改多变量模糊控制器的控制规则和模糊推理过程,并提出了神经元网络无教师自学习的解决方案,避免了控制器在实际应用过程中训练样本获取的复杂过程。经过Labwindows软件平台的验证,该模糊控制器在控制规则自动生成、多变量关系解耦、学习收敛速率等方面具有很好的性能,并在非线性时变系统的应用中取得了良好的控制效果。
关键词: 自动控制技术 模糊神经 多变量 无教师自学习 自适应
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Multivariable Adaptive Fuzzy Controller
Abstract:This paper study a new design of a multivariable adaptive fuzzy controller,using one single-layer neural network to learn, create and modify multi-variable control rules and fuzzy inference process of the fuzzy controller, and put forward solutions for Unsupervised Learning of neural network to avoid the complex process of getting training samples.After validation simulation on the Labwindows software platform,the result shows that the controller had good performance in control rules automatic generation, multivariate relationship decoupling and learning convergence rate,achieving good control effects in nonlinear time-varying systems.
Keywords: Automatic control technology Fuzzy Neural Multi-variable Unsupervised Learning adaptive
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