time control module (MathWorks Inc)
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Time Control Module, supplied by MathWorks Inc, used in various techniques. Bioz Stars score: 96/100, based on 1965 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
https://www.bioz.com/product/time+controller+module/Simulink+Real-Time/pm40006216-243-10-15
Average 96 stars, based on 1965 article reviews
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Control:Article Title: Nonlinear modeling and control approach to magnetic levitation ball system using functional weight RBF network-based state-dependent ARX model Article Snippet: A hybrid model, which adopts a radial basis function (RBF) neural networks with functional weights (FWRBF) to approximate the coefficients of the state-dependent AutoRegressive model with eXogenous input variables (SD-ARX), is built for modeling a magnetic levitation ball system and is referred to as the functional weight RBF nets-based ARX (FWRBF-ARX) model.. This model structure, which may be identified by using the historical input/output data, inherits both the advantages of the FWRBF networks in function approximation and of the state-dependent ARX models in description of nonlinear dynamics.. Due to the structured characteristics of the FWRBF-ARX model, an offline structured nonlinear parameter optimization method (SNPOM) is applied to identify the model structure and parameters. Sampling:Article Title: Nonlinear modeling and control approach to magnetic levitation ball system using functional weight RBF network-based state-dependent ARX model Article Snippet: A hybrid model, which adopts a radial basis function (RBF) neural networks with functional weights (FWRBF) to approximate the coefficients of the state-dependent AutoRegressive model with eXogenous input variables (SD-ARX), is built for modeling a magnetic levitation ball system and is referred to as the functional weight RBF nets-based ARX (FWRBF-ARX) model.. This model structure, which may be identified by using the historical input/output data, inherits both the advantages of the FWRBF networks in function approximation and of the state-dependent ARX models in description of nonlinear dynamics.. Due to the structured characteristics of the FWRBF-ARX model, an offline structured nonlinear parameter optimization method (SNPOM) is applied to identify the model structure and parameters. |
