Single iterative algorithm with global feedback for integrated system optimisation and parameter estimation of large scale industrial processes: optimality, convergence and simulation

A single iterative algorithm with a global feedback structure for the integrated system optimisation and parameter estimation (ISOPE) of large scale industrial processes is investigated. An augmentation technique is employed to reduce the sensitivity of the algorithm to the iterative gain selection and to improve the convergence. The advantage of using a global feedback structure is that the convergence of the real performance tends to be very fast. Optimality and convergence of the algorithm both with and without augmentation were investigated. Computer simulations were performed to demonstrate the features of the algorithm.