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| 2. |
- Bombois, Xavier, et al.
(författare)
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Optimal identification experiment design for the interconnection of locally controlled systems
- 2018
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Ingår i: Automatica. - : Elsevier. - 0005-1098 .- 1873-2836. ; 89, s. 169-179
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Tidskriftsartikel (refereegranskat)abstract
- This paper considers the identification of the modules of a network of locally controlled systems (multi-agent systems). Its main contribution is to determine the least perturbing identification experiment that will nevertheless lead to sufficiently accurate models of each module for the global performance of the network to be improved by a redesign of the decentralized controllers. Another contribution is to determine the experimental conditions under which sufficiently informative data (i.e. data leading to a consistent estimate) can be collected for the identification of any module in such a network.
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| 3. |
- Larsson, Christian A., et al.
(författare)
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An application-oriented approach to dual control with excitation for closed-loop identification
- 2016
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Ingår i: European Journal of Control. - : Elsevier. - 0947-3580 .- 1435-5671. ; 29, s. 1-16
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Tidskriftsartikel (refereegranskat)abstract
- Identification of systems operating in closed loop is an important problem in industrial applications, where model-based control is used to an increasing extent. For model-based controllers, plant changes over time eventually result in a mismatch between the dynamics of any initial model in the controller and the actual plant dynamics. When the mismatch becomes too large, control performance suffers and it becomes necessary to re-identify the plant to restore performance. Often the available data are not informative enough when the identification is performed in closed loop and extra excitation needs to be injected. This paper considers the problem of generating such excitation with the least possible disruption to the normal operations of the plant. The methods explicitly take time domain constraints into account. The formulation leads to optimal control problems which are in general very difficult optimization problems. Computationally tractable solutions based on Markov decision processes and model predictive control are presented. The performance of the suggested algorithms is illustrated in two simulation examples comparing the novel methods and algorithms available in the literature.
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| 4. |
- 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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