Efficient predictive control integrated with economic optimisation based on neural models

Abstract

This paper presents a predictive control scheme integrated with economic optimisation. Two neural models are used: a dynamic one (for the control subproblem) and a steady-state one (for the economic optimisation subproblem). The algorithm is computationally efficient because it needs solving on-line only one quadratic programming problem. Unlike the classical control system structure, the necessity of repeating two nonlinear optimisation problems at each sampling instant is avoided. © 2008 Springer-Verlag Berlin Heidelberg.