| 1. |
- Mesbah, A., et al.
(författare)
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A unified experiment design framework for detection and identification in closed-loop performance diagnosis
- 2012
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Ingår i: Decision and Control (CDC), 2012 IEEE 51st Annual Conference on. - : IEEE. ; , s. 2152-2157
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Konferensbidrag (refereegranskat)abstract
- This paper presents a least-costly experiment design framework for closed-loop performance diagnosis using prediction error identification. The performance diagnosis methodology consists in verifying whether an identified model of the true system lies in a performance-related region of interest. The experiment design framework minimizes the overall excitation cost incurred for detecting the cause of the performance drop and re-identifying the system dynamics when the degraded performance is due to control-relevant system changes. The optimal design of excitation signals is performed for a desired detection rate and a pre-specified level of accuracy required for the re-identified model.
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| 2. |
- Potters, M. G., et al.
(författare)
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Optimal Experiment Design in Closed Loop with Unknown, Nonlinear and Implicit Controllers using Stealth Identification
- 2014
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Ingår i: 2014 European Control Conference, ECC 2014. - : IEEE. - 9783952426913 ; , s. 726-731
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Konferensbidrag (refereegranskat)abstract
- We present a novel optimal experiment design method that is applicable to linear time-invariant systems regulated by unknown, nonlinear and implicitly-defined controllers. Current methods require an explicit expression for the controller in order to construct the optimal excitation spectrum. Consequently, these are limited to linearly-controlled systems. The identification scheme suggested in this paper circumvents the aforementioned requirement by ensuring that the excitation signal remains unnoticed by the controller, i.e., the identification data is gathered in an open-loop fashion. Our theoretical analysis is complemented with a numerical study on a six-parameter, single-input single-output linear system controlled by an MPC. We find that our method generates least-costly excitation signals which deliver identified models that lie close to the true system whilst honoring quality constraints, validating the novel optimal experiment design framework.
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| 3. |
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| 4. |
- Hassel, B. I., et al.
(författare)
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Single cube apparatus - Shear properties determination and shear strain variation in natural density gradient materials
- 2009
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Ingår i: ICCM-17 17th International Conference on Composite Materials. - : International Committee on Composite Materials.
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Konferensbidrag (refereegranskat)abstract
- Transversal shear of softwoods was studied with the single cube apparatus (SCA). Full field strain data and FEA were used to validate the device. Once a close to pure shear strain region was confirmed, the relationship between shear strain and radial density gradient was obtained; finally an improved FE model was created.
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| 5. |
- Özkan, Leyla, et al.
(författare)
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Advanced autonomous model-based operation of industrial process systems (Autoprofit) : Technological developments and future perspectives
- 2016
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Ingår i: ANNUAL REVIEWS IN CONTROL. - : Elsevier. - 1367-5788. ; 42, s. 126-142
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Forskningsöversikt (refereegranskat)abstract
- Model-based operation support technology such as Model Predictive Control (MPC) is a proven and accepted technology for multivariable and constrained large scale control problems in process industry. Despite the growing number of successful implementations, the low level of operational efficiency of MPC is an existing problem, specifically the lack of advanced maintenance technology. To this end, within the EU FP 7 program, a project (Autoprofit (1)) has been executed to advance the level of autonomy and automated maintenance of MPC technology. Taking linear model-based technology as a starting point, in the project a philosophy has been developed for autonomous performance monitoring, diagnosis, experiment design, model adaptation and controller re-tuning, that is driven by economic criteria in each step, working towards an operation support system in which effective maintenance and adaptation of MPC controllers becomes feasible. In this development, challenging research questions have been addressed in the areas of on-line performance monitoring and diagnosis, least costly experiment design, automated adaptation of models, and auto-tuning, and new fundamental techniques have been developed. Although a full fledge and industrially proven (semi-)automated system is not yet realised, parts of the on-line system have been implemented and validated on real life cases provided by the industrial partners, showing that the formulated objectives are within reach.
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