Efficient Predictive Control Integrated with Economic Optimisation Based on Neural Models

Authors:
Maciej Ławryńczuk;Piotr Tatjewski
Affiliations:
Institute of Control and Computation Engineering, Warsaw University of Technology, Warsaw, Poland 00-665;Institute of Control and Computation Engineering, Warsaw University of Technology, Warsaw, Poland 00-665
Venue:
ICAISC '08 Proceedings of the 9th international conference on Artificial Intelligence and Soft Computing
Year:
2006

Citing 4
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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.