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논문 기본 정보

자료유형
학술대회자료
저자정보
Yul Yunazwin Nazaruddin (Institut Teknologi Bandung) Abdullah Nur Aziz (Institut Teknologi Bandung) Wisnu Sudibjo (Institut Teknologi Bandung)
저널정보
제어로봇시스템학회 제어로봇시스템학회 국제학술대회 논문집 ICCAS 2008
발행연도
2008.10
수록면
1,921 - 1,926 (6page)

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In heat generation process, performance improvement is a critical factor and essential. An alternative solution is by designing an advanced combustion controller based on neural-predictive control strategy. However, for accomplishing such goal it requires adequate boiler model as well as combustion model. Although heat transfer and combustion processes in boiler are too complex to be analytically described with mathematical model, it can be approximated by artificial neural network model. This paper presents an alternative strategy to model the boiler and combustion process as well as proposes an advanced control strategy that takes the advantage of artificial neural network’ ability as a universal function approximation. A feedforward neural network algorithm is applied to construct the models and the gradient descent technique seeks the optimal network weights, from which the nonlinear predictive control law under the reduced excess air level is derived. Direct application of this control strategy to real-time data taken from a running boiler system at an oil refinery plant demonstrated the benefit of the algorithm to improve the boiler combustion performance.

목차

Abstract
1. INTRODUCTION
2. BOILER COMBUSTION SYSTEMS AND THE CONTROL PROBLEM
3. MODELING AND CONTROL STRATEGY
4. RESULTS AND EVALUATION
5. COST SAVING CALCULATION
6. CONCLUSIONS
ACKNOWLEDGEMENTS
REFERENCES

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UCI(KEPA) : I410-ECN-0101-2014-569-000986162