DocumentCode :
878733
Title :
Predictive control for the ALSTOM gasifier problem
Author :
Seyab, R.K.A. ; Cao, Y. ; Yang, S.H.
Author_Institution :
School of Engineering, Cranfield Univ., Bedford, UK
Volume :
153
Issue :
3
fYear :
2006
fDate :
5/9/2006 12:00:00 AM
Firstpage :
293
Lastpage :
301
Abstract :
Model predictive control (MPC) has become the first choice of control strategy in many cases especially in the process industry because it is intuitive and can explicitly handle MIMO (multiple input multiple output) systems with input and output constraints. The authors implemented a simple MPC algorithm based on the state space formulation to control the ALSTOM gasifier. Among three operating conditions of the plant, 0% load condition is identified as the worst case. A linearised state space model at 0% load condition of the non-linear plant is adopted as the internal model for performance prediction. Because of this choice, the control system comfortably achieves performance requirements at the most difficult load condition. Meanwhile, the case study shows that the model is also adequate to pass all tests under other load conditions specified in the benchmark problem. The MPC algorithm uses standard formulation and off-the-shelf software with a few tunable parameters. Thus, it is easy to implement and to tune to achieve satisfactory performance.
Keywords :
MIMO systems; nonlinear control systems; predictive control; process control; state-space methods; ALSTOM gasifier problem; MIMO system; model predictive control; multiple input multiple output system; nonlinear process; process industry; state space formulation;
fLanguage :
English
Journal_Title :
Control Theory and Applications, IEE Proceedings -
Publisher :
iet
ISSN :
1350-2379
Type :
jour
DOI :
10.1049/ip-cta:20050049
Filename :
1610475
Link To Document :
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