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A robustly stabilizing model predictive control strategy of stable and unstable processes

机译:稳定和不稳定过程的鲁棒稳定模型预测控制策略

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摘要

This paper deals with the development of a robust model predictive control strategy with guarantee of stability, applicable to the stable and unstable processes. The model uncertainty is assumed to be described by a discrete set of linear models (multi-plant uncertainty), and the robustness is achieved by assembling cost-contracting constraints for all the possible models in the uncertainty domain. On the basis of a suitable state-space model description, an offset free control law is obtained by means of a one-step optimization formulation. The usefulness of the method proposed here is illustrated with control simulations of an unstable reactor system taken from the literature. (C) 2016 Elsevier Ltd. All rights reserved.
机译:本文研究了具有稳定性的鲁棒模型预测控制策略的发展,适用于稳定和不稳定过程。假定模型不确定性由一组离散的线性模型(多工厂不确定性)描述,并且通过在不确定性域中组合所有可能模型的成本约束来实现鲁棒性。在适当的状态空间模型描述的基础上,通过一步优化公式获得无偏移控制律。此处提出的方法的有效性通过从文献中获得的不稳定反应器系统的控制仿真进行了说明。 (C)2016 Elsevier Ltd.保留所有权利。

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