Time delay estimation of soft-sensor model based on hybrid differential evolution algorithm
Time delay estimation is one of the most important issues in system control and signal processing.Through establishing an appropriate fitness function,the time delay estimation of soft-sensor model could be formulated as a multi-dimension nonlinear functional optimization problem,which could be solved by hybrid differential evolution(HDE)algorithm.Numerical simulation results on two benchmarks demonstrated the effectiveness and robustness of HDE.Taking a crude atmospheric distillation unit in oil refinery as an example,a numerical application of the soft-sensor model for the kerosene flash point was made.The application results demonstrated that the accuracy of soft-sensor model was greatly improved with the introduction of time delay estimation.Besides,the effectiveness of the proposed HDE was confirmed.