The objective of this thesis is to develop algorithms for application-oriented input design. This procedure takes the model application into account when designing experiments for system identification. This thesis is divided into two parts. The first part considers the theory of application-oriented input design, with special attention to Model Predictive Control (MPC). We start by studying how to find a convex approximation of the set of models that result in acceptable control performance using analytical methods when controllers with no closed-form control law, for e.g., MPC are employed. The application-oriented input design is formulated in time domain to enable handling of signals constraints. The framework is extended to closed-loop systems where two cases are considered i.e., when the plant is controlled by a general but known controller and for the case of MPC. To this end, an external stationary signal is designed via graph theory. Different sources of uncertainty in application-oriented input design are investigated and a robust application-oriented input design framework is proposed. The second part of this thesis is devoted to the problem of estimating the number of occupants based on the information available to HVAC systems in buildings. The occupancy estimation is first formulated as a two-tier problem. In the first tier, the room dynamic is identified using temporary measurements of occupancy. In the second tier, the identified model is employed to formulate the problem as a fused-lasso problem. The proposed method is further developed to be used as a multi-room estimator using a physics-based model. However, since it is not always possible to collect measurements of occupancy, we proceed by proposing a blind identification algorithm which estimates the room dynamic and occupancy, simultaneously. Finally, the application-oriented input design framework is employed to collect data that is informative enough for occupancy estimation purposes. / <p>QC 20170620</p>
Identifer | oai:union.ndltd.org:UPSALLA1/oai:DiVA.org:kth-209021 |
Date | January 2017 |
Creators | Ebadat, Afrooz |
Publisher | KTH, Reglerteknik, Stockholm |
Source Sets | DiVA Archive at Upsalla University |
Language | English |
Detected Language | English |
Type | Doctoral thesis, monograph, info:eu-repo/semantics/doctoralThesis, text |
Format | application/pdf |
Rights | info:eu-repo/semantics/openAccess |
Relation | TRITA-EE, 1653-5146 ; 2017:058 |
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