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Optimal Adaptive Control of an Ash Stabilization Batch Mixing Process using Change Detection

Svantesson, T. and Olsson, Gustaf LU (2000) IEEE International Conference on Control Applications, 2000 In Control Applications, 2000. Proceedings of the 2000 IEEE International Conference on
Abstract
We present an optimal adaptive controller that is used to regulate the chemical process of wood ash stabilization (WAS). The model parameters of the time-varying process dynamics are estimated using recursive least squares (RLS). At each batch an auto-tuning sequence produced with the controller disabled is carried through in order to obtain a good estimate of the process dynamics. After the auto-tuning sequence is completed, a generalized predictive controller is enabled to control the WAS process. The control objective is to regulate the normalized effective power Pe(t) to the level Pe crit that represents the critical rate of useful work being performed by the three-phase asynchronous machine used for the stirrer drive. Hence, Pecrit... (More)
We present an optimal adaptive controller that is used to regulate the chemical process of wood ash stabilization (WAS). The model parameters of the time-varying process dynamics are estimated using recursive least squares (RLS). At each batch an auto-tuning sequence produced with the controller disabled is carried through in order to obtain a good estimate of the process dynamics. After the auto-tuning sequence is completed, a generalized predictive controller is enabled to control the WAS process. The control objective is to regulate the normalized effective power Pe(t) to the level Pe crit that represents the critical rate of useful work being performed by the three-phase asynchronous machine used for the stirrer drive. Hence, Pecrit also represents the desired mixture viscosity. If more water is added to the stabilization process after Pecrit has been reached, one will obtain a mixture useless for granular material. To cope with this problem, change detection is used to reach the desired level Pecrit without any pre-determined set-point. Two methods are evaluated; a probing strategy and the geometric moving average test, both adequate for successful implementation. The used control strategies are presented and off-line simulations with a model of the physical process evaluate the control performance (Less)
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author
organization
publishing date
type
Chapter in Book/Report/Conference proceeding
publication status
published
subject
keywords
adaptive control batch processing (industrial) closed loop systems least squares approximations mixing predictive control process control recursive estimation tuning
in
Control Applications, 2000. Proceedings of the 2000 IEEE International Conference on
conference name
IEEE International Conference on Control Applications, 2000
external identifiers
  • Scopus:0034474822
ISBN
0-7803-6562-3
DOI
10.1109/CCA.2000.897408
language
English
LU publication?
yes
id
70db203a-abb7-4b0f-8ffc-21606cebc1b2 (old id 4358647)
date added to LUP
2014-03-18 09:15:06
date last changed
2016-10-13 04:51:43
@misc{70db203a-abb7-4b0f-8ffc-21606cebc1b2,
  abstract     = {We present an optimal adaptive controller that is used to regulate the chemical process of wood ash stabilization (WAS). The model parameters of the time-varying process dynamics are estimated using recursive least squares (RLS). At each batch an auto-tuning sequence produced with the controller disabled is carried through in order to obtain a good estimate of the process dynamics. After the auto-tuning sequence is completed, a generalized predictive controller is enabled to control the WAS process. The control objective is to regulate the normalized effective power Pe(t) to the level Pe crit that represents the critical rate of useful work being performed by the three-phase asynchronous machine used for the stirrer drive. Hence, Pecrit also represents the desired mixture viscosity. If more water is added to the stabilization process after Pecrit has been reached, one will obtain a mixture useless for granular material. To cope with this problem, change detection is used to reach the desired level Pecrit without any pre-determined set-point. Two methods are evaluated; a probing strategy and the geometric moving average test, both adequate for successful implementation. The used control strategies are presented and off-line simulations with a model of the physical process evaluate the control performance},
  author       = {Svantesson, T. and Olsson, Gustaf},
  isbn         = {0-7803-6562-3},
  keyword      = {adaptive control batch processing (industrial) closed loop systems least squares approximations mixing predictive control process control recursive estimation tuning},
  language     = {eng},
  series       = {Control Applications, 2000. Proceedings of the 2000 IEEE International Conference on},
  title        = {Optimal Adaptive Control of an Ash Stabilization Batch Mixing Process using Change Detection},
  url          = {http://dx.doi.org/10.1109/CCA.2000.897408},
  year         = {2000},
}