IOP Conference Series Materials Science and Engineering · 2013 · 19 citations · 5 references
EngineeringIndustrial EngineeringHeating SystemNonlinear System IdentificationParameter IdentificationSystems EngineeringModeling And SimulationThermal ModelingParametric Identification TechniqueIndustrial Heating SystemComputer EngineeringLoss FunctionHeat TransferSystem IdentificationEnergy PredictionEnergy ModelingProcess ControlThermal EngineeringModel Identification
This paper proposed a systematic approach to select a mathematical model for an industrial heating system by adopting system identification techniques with the aim of fulfilling the design requirement for the controller. The model identification process will begin by collecting real measurement data samples with the aid of MATLAB system identification toolbox. The criteria for selecting the model that could validate model output with actual data will based upon: parametric identification technique, picking the best model structure with low order among ARX, ARMAX and BJ, and then applying model estimation and validation tests. Simulated results have shown that the BJ model has been best in providing good estimation and validation based upon performance criteria such as: final prediction error, loss function, best percentage of model fit, and co-relation analysis of residual for output.
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System identification—Theory for the user
Naresh K. Sinha · Automatica · 1989 · 9.2K citations
System Identification—theory, Engineering, Systems Engineering +4