摘要：AbstractIn this paper, a continuous stirred tank reactor (CSTR) is identified in closed loop using a direct prediction error based approach. This common process control system is represented by Hammerstein model, a memoryless non-linearity in cascade with a linear dynamic subsystem. In direct closed-loop identification, the process and noise models are identified using an open-loop prediction error minimization approach. The noise model is represented by an Auto Regressive Integrated Moving Average (ARIMA) model, as disturbances in chemical processes are often non-stationary, consisting of sequences of random steps. The Hammerstein system is identified in the presence of this non-stationary disturbance via a differencing based technique. Finally, simulation examples, validation tests and results comparisons are provided.
关键词：KeywordsHammerstein modelPrediction Error MethodSeparable Least SquaresNonlinear System IdentificationInstrumental Variable Method
