Nonlinear model predictive control for the ALSTOM gasifier
نویسندگان
چکیده
منابع مشابه
Nonlinear Model Predictive Control for the Alstom Gasifier
In this work a nonlinear model predictive control based on Wiener model has been developed and used to control the ALSTOM gasifier. The 0% load condition was identified as the most difficult case to control among three operating conditions. A linear model of the plant at 0% load is adopted as a base model for prediction. A nonlinear static gain represented by a feedfor-ward neural network was i...
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Model predictive control has become a first choice control strategy in industry because it is intuitive and can explicitly handle MIMO linear and nonlinear systems with the presence of variable constraints and interactions. In this work a nonlinear state-space model has been developed and used as the internal model in predictive control for the ALSTOM gasifier. A linear model of the plant at 0%...
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Proportional-Integral-Plus (PIP) control methods are applied to the ALSTOMBenchmark Challenge II. The approach utilises a data-based combined model reduction and linearisation step, which plays an essential role in satisfying the design specifications – these are comfortably met for all three operating conditions.
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Neural Network Model Based Predictive Control (MPC) has become a good choice of control strategy in many cases especially in the process industry because it could face non linearities and cross coupling variables [6], being modeling the first step to achieve this end. The model of a gasifier, provided by ALSTOM Power Technology Centre, is of an industrial standard and has been validated against...
متن کاملThe Analysis and Control of the Alstom Gasifier Benchmark Problem
This paper considers the analysis and controller design for the ALSTOM gasifier system. The inherent properties of this highly coupled multivariable system are studied. Minimal realizations of the system models at the three operating points to be considered are determined, and the numerical condition of the system is improved. Model order reduction methods are applied to simplify the subsequent...
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ژورنال
عنوان ژورنال: Journal of Process Control
سال: 2006
ISSN: 0959-1524
DOI: 10.1016/j.jprocont.2006.03.003