A new approach to establish a steady-state model of an industrial process

This paper details with the steady-state modelling of an industrial process. Under weak conditions, an estimate of the steady-state model is formed from the estimated parameters of an approximate linear dynamic model. For a class of nonlinear slow time-varying processes, the consistency of this estimate is proved Further, asymptotic distribution of the estimation error is analysed and the asymptotic rate of convergence is investigated. It is notable that, under acceptable conditions, robustness on the structure of the approximate linear dynamic model is achieved. Simulation examples show that this new identification approach is efficient and reliable for the steady-state modelling of an industrial process.