通风系统的过程建模及多变量模型预测控制的实现

J. Hrbček, Juraj Spalek, V. Simák
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引用次数: 9

摘要

预测控制似乎是一种很有前途的方法,可以帮助改善现有通风系统在公路隧道中的应用。预测控制的优势主要在于它既能解决SISO任务,又能解决MIMO任务,能够广泛地考虑过程变化的动态性,补偿可测量和不可测量故障的影响,并将任务制定为考虑控制动作的极限条件、控制动作的变化和输出变量的优化控制任务。现有通风系统的特征数据可用于分析和识别系统并创建其模型。然后,可以设计通风预测控制,使其能够预测污染物浓度并优化系统运行。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Process model and implementation the multivariable model predictive control to ventilation system
Predictive control seems to be a promising approach that can help to improve properties of existing ventilation systems applied in road tunnels. Advantages of predictive control result mainly from its ability to solve both SISO and MIMO tasks, to have regard for dynamics of process changes in a broad extent, to compensate effect of measurable and non-measurable failures and to formulate the task as an optimization control task considering limiting conditions of control actions, changes of control actions and output variables. Data characterizing the existing ventilation system can be used to analyze and identify the system and create its models. Thereafter the predictive control of ventilation can be designed enabling to predict concentrations of pollutants and optimize system operation.
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