Model Based Double Iterative Strategy for Integrated System Optimisation and Parameter Estimation of Large Scale Industrial Processes

Abstract

A novel hierarchical structure is described which determines the optimum steady state operation of interconnected industrial processes inspite of deficiencies in the mathematical model. The technique is of an iterative type and involves successive solutions of system optimization and model parameter estimation problems, utilizing information feedback from the real process. Particular emphasis is given to a strategy where the coordination task is divided into two nested iterative loops. The inner loop involves model based computations only, while the outer loop requires measurements from the real process. It is shown that this model based double iterative strategy has an important practical advantage in that it reduces the required number of set point changes to real subprocesses in order to achieve optimality. The paper investigates the optimality and convergence conditions of the technique and gives a simple simulation example to illustrate the method.