MPC Design for an Auditorium Building Using Data Driven Modeling. Issue 20 (2022)

• Record Type: Journal Article
• Authors: Paschke, Fabian; Huang, Chenzi; Seidel, Stephan
• Is Part Of: IFAC-PapersOnLine. Volume 55:Issue 20(2022)
• Page Start: 103
• Page End: 108
• Publication Date: 2022
• Subjects: Predictive control -- Process identification -- Building systems -- HVAC control; Automatic control -- Periodicals; 629.805
• DOI: 10.1016/j.ifacol.2022.09.079
• Languages: English
• ISSNs: 2405-8963

Abstract

Abstract: This paper describes the design of a model predictive controller (MPC) for preheating/-cooling of an auditorium building with a central air handling unit (AHU). The data-based approach uses system identification to estimate a low order nonlinear MPC model. The data used for identification is generated by simulation of a high order process model that was developed in Modelica using the open source Buildings library. This model is further used for validation of the predictive controller within Matlab/Simulink using Functional Mock-up Interface (FMI). Advantages of MPC compared to a conventional control strategy are simulatively proven using co-simulation, where an overall cost reduction of approx. 25% was achieved.