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

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Author

Summary, in English

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

Publishing year

2000

Language

English

Publication/Series

Control Applications, 2000. Proceedings of the 2000 IEEE International Conference on

Document type

Conference paper

Topic

  • Other Electrical Engineering, Electronic Engineering, Information Engineering

Keywords

  • adaptive control batch processing (industrial) closed loop systems least squares approximations mixing predictive control process control recursive estimation tuning

Conference name

IEEE International Conference on Control Applications, 2000

Conference date

2000-09-25 - 2000-09-27

Conference place

Anchorage, Alaska, United States

Status

Published

ISBN/ISSN/Other

  • ISBN: 0-7803-6562-3