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Application of multi-model adaptive control to pulping processes

University of British Columbia

In this thesis, the theory of Multi-Model Adaptive Control is applied to pulping processes, particularly for wood species compensation and identification, and dead-time compensation. Wood species identification is performed on a kraft pulping process whose kinetics are described by the Hatton’ s equations where the ratios of the different wood species in the incoming feed stream are identified on-line by a recursive least-squares based estimation algorithm. Upon wood species identification, a multi-model adaptive controller takes action to compensate for the variability in the wood chips supply content and to control the kappa number. Dead-time compensation is applied to a chlorination tower in a bleaching process with chlorine and chlorine dioxide. The corresponding mass balance equations are developed. The process is simulated, sampled, and identified in open-loop. A multi-model adaptive controller is utilized in closed-loop to compensate for the variations in the pulp quality and transport time delay and to control the bleaching kappa number. The controller’s performance is compared against an adaptive controller which is coupled with a recursive least-squares based algorithm and the Fixed Model Variable Regression Estimation algorithm to compensate for the same variations.

Thesis/Dissertation

application/pdf

2009-02-23

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http://hdl.handle.net/2429/4935

Electrical and Computer Engineering

University of British Columbia

UBCV

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