An Algorithm for Tuning NMPC Controllers with Application to Chemical Processes

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• 作者：Federico Lozano Santamaría ; Jorge M. Gómez
• 刊名：Industrial & Engineering Chemistry Research
• 出版年：2016
• 出版时间：August 31, 2016
• 年：2016
• 卷：55
• 期：34
• 页码：9215-9228
• 全文大小：702K
• 年卷期：0
• ISSN：1520-5045

文摘

The advantages of linear/nonlinear model predictive control (N)MPC for dealing with the multiple input multiple output problem, for performing optimization and for handling constraints are well-known and because of that it has been applied widely in the chemical industry. However, there is a recurrent problem for this kind of controllers and it is how to define the best tuning parameters to achieve a good closed-loop response. This is an open question for research even when the common practice is to define the (N)MPC tuning parameters by trial and error or by the expertise of the control engineer. There are some works that propose a systematic definition of the (N)MPC tuning parameters, but most of them are restricted to certain prediction models or do not define all the tuning parameters. This papers presents a general tuning algorithm for (N)MPC controllers that allows the systematic definition of all the tuning parameter and it is not restricted to a specific prediction model or to a problem formulation. It is based on multiobjective optimization for the definition of the objective function weights and on the optimization of a closed loop performance index for the definition of the horizon lengths. Three cases of chemical processes are considered in detail to illustrate the application and advantages of the proposed (N)MPC tuning algorithm.