| 1. |
- Ding, Limei, et al.
(författare)
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Application of reduced models for robust control and state estimation of a distributed parameter system
- 2009
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Ingår i: Journal of Process Control. - : Elsevier BV. - 0959-1524 .- 1873-2771. ; 19:3, s. 539-549
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Tidskriftsartikel (refereegranskat)abstract
- This paper studies the application of reduced models of a distributed parameter system for robust process control and state estimation. We take the approach of integrating model reduction, parameter identification, and model uncertainty analysis, in purpose to find an appropriate trade-off between complexity and robust performance. The application example is the temperature system in a continuous paper pulp digester. Physical modeling of this process results in coupled linearized partial differential equations which are then reduced into low-order nominal process models using an orthogonal collocation approximation method.Two different approaches to obtaining a model uncertainty description are adapted for use on a distributed parameter system with low-order nominal model and shown to produce similar results when tested with measurement data. It is also demonstrated how this uncertainty description, in combination with the reduced model, may be used for robust control design and verification of the control performance on the distributed parameter system.Finally, the possibility of estimating the distributed process state using a state observer for the reduced process is demonstrated. Measurements of the process state in a certain position is available and is shown to agree with the estimated state at the same position.
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| 2. |
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| 3. |
- Ding, Limei, et al.
(författare)
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Model parameter estimation of simplified linear models for a continuous paper pulp digester
- 2007
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Ingår i: Journal of Process Control. - : Elsevier BV. - 0959-1524 .- 1873-2771. ; 17:2, s. 115-127
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Tidskriftsartikel (refereegranskat)abstract
- A physical model of a continuous paper pulp digester is simplified and two subprocesses selected from the digester are modelled by coupled linear partial differential equations. This study focuses on the parameter identification of the simplified linear models. Finite-dimensional approximation of the model is made and a software package developed for identification of distributed parameter processes is applied. This identification system is developed for flexibility to allow identification for different choices of subprocesses and process variables. Unknown parameters of the subprocess models are estimated and the results are illustrated by process simulation and model validation.
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| 4. |
- Ding, Limei, et al.
(författare)
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Physical model parameter estimation of a nonlinear process
- 2007
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Ingår i: Proceedings of the 2006 IEEE International Conference on Control Applications Applications. - Piscataway, NJ : IEEE Communications Society. - 0780397959 ; , s. 2933-2938
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Konferensbidrag (refereegranskat)abstract
- A physical model of a nonlinear subprocess in a continuous paper pulp digester is discussed and simplified. Model approximation is carried out in order to produce a simple linear model to be used for unknown parameter estimation of the physical model. The Taylor series expansion and the orthogonal collocation method are applied for the model linearization and model lumping, respectively. The reduced model is expressed as a standard state space form. The model parameters are estimated in the least squares sense, and the parameters retain their own physical meanings. The results of the parameter estimation are discussed and the model is verified using validation data.
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