Comments: Gradient auto-tuned Takagi-Sugeno Fuzzy Forward control of a HVAC system using predicted mean vote index

Gradient auto-tuned Takagi-Sugeno Fuzzy Forward control of a HVAC system using predicted mean vote index

Controllers of HVAC systems are expected to be able to manipulate the inherent nonlinear characteristics of these large scale systems that also have pure lag times, big thermal inertia, uncertain disturbance factors and constraints. In addition, indoor thermal comfort is affected by both temperature...

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Bibliographic Details
Main Authors:	Homod R.Z., Sahari K.S.M., Almurib H.A.F., Nagi F.H.
Other Authors:	36994633500
Format:	Article
Published:	2023
Subjects:	Building energy control HVAC system PMV signal reference TS Fuzzy identification TSFF control Cascade control systems Climate control Control nonlinearities Newton-Raphson method Building energy Cascade control Control methods Control objectives Control strategies Disturbance factors Gauss-Newton methods Gradient algorithm Indoor thermal comfort Lag time Non-linear regression Nonlinear characteristics Offline Predicted mean vote Residential loads Save energy T S models T-S fuzzy Takagi-sugeno Thermal inertia Thermal parameters Thermal sensitivity Uncertainty effects Weather conditions Humidity control
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Gradient auto-tuned Takagi-Sugeno Fuzzy Forward control of a HVAC system using predicted mean vote index

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