Approaches to the optimizing control problem

Ellis, J. E.; Kambhampati, C; Sheng, G; Roberts, P. D.

Abstract

The selection of the steady-state controls which enable a system to operate in an optimum manner is the optimizing control problem. An examination of direct and adaptive model-based approaches to this problem is made. In the direct approach, system measurements are used directly within an optimization procedure while, with the adaptive model-based techniques, an updated model is used for the optimization problem and the results of the model-based problem are applied to the system. Here, due to its recognized efficiency among established optimization algorithms, a conjugate direction method is adopted for the direct approach. For the model-based approach, two different techniques are described. A rationalized form of modified two-step method is presented along with a new method based on an approximate linear model. An assessment of the efficiency of the various methods is made through the simulation of a gas mixer system. The direct method is seen to be unrealistic while, for the system considered, the approximate linear model approach is seen to be superior to the modified two-step method.

Citation

Ellis, J. E., Kambhampati, C., Sheng, G., & Roberts, P. D. (1988). Approaches to the optimizing control problem. International Journal of Systems Science, 19(10), 1969-1985. https://doi.org/10.1080/00207728808964092

• Journal Article Type: Article
• Acceptance Date: Jun 8, 1987
• Online Publication Date: May 31, 2007
• Publication Date: Dec 31, 1988
• Journal: International Journal of Systems Science
• Print ISSN: 0020-7721
• Publisher: Taylor and Francis
• Peer Reviewed: Peer Reviewed
• Volume: 19
• Issue: 10
• Pages: 1969-1985
• DOI: https://doi.org/10.1080/00207728808964092
• Keywords: Control and Systems Engineering; Theoretical Computer Science; Computer Science Applications
• Public URL: https://hull-repository.worktribe.com/output/409671
• Publisher URL: https://www.tandfonline.com/doi/abs/10.1080/00207728808964092