期刊
JOURNAL OF PROCESS CONTROL
卷 23, 期 9, 页码 1306-1319出版社
ELSEVIER SCI LTD
DOI: 10.1016/j.jprocont.2013.08.008
关键词
Semi-batch reactors; Model predictive control; Robust control; Optimization; Uncertainty
资金
- European Union [FP7-ICT-2009-4 248940]
- Deutsche Forschungsgemeinschaft (DFG, German Research Council) [EN 152/39-1]
Model predictive control (MPC) has become one of the most popular control techniques in the process industry mainly because of its ability to deal with multiple-input multiple-output plants and with constraints. However, in the presence of model uncertainties and disturbances its performance can deteriorate. Therefore, the development of robust MPC techniques has been widely discussed during the last years, but they were rarely, if at all, applied in practice due to the conservativeness or the computational complexity of the approaches. In this paper, we present multi-stage NMPC as a promising robust non-conservative nonlinear model predictive control scheme. The approach is based on the representation of the evolution of the uncertainty by a scenario tree, and leads to a non-conservative robust control of the uncertain plant because the adaptation of future inputs to new information is taken into account. Simulation results show that multi-stage NMPC outperforms standard and min-max NMPC under the presence of uncertainties for a semi-batch polymerization benchmark problem. In addition, the advantages of the approach are illustrated for the case where only noisy measurements are available and the unmeasured states and the uncertainties have to be estimated using an observer. It is shown that better performance can be achieved than by estimating the unknown parameters online and adapting the plant model. (C) 2013 Elsevier Ltd. All rights reserved.
作者
我是这篇论文的作者
点击您的名字以认领此论文并将其添加到您的个人资料中。
推荐
暂无数据