Indirect Adaptive Model Predictive Control of a Mechanical Pulp Bleaching Process

J.H. Taylor and K.M. Akida (Canada)


Indirect adaptive control, predictive control, on-line identification, pulp bleaching process, variable time delay.


The classic way to control a process, in a model based framework, is to obtain a model of the system and then use it for the design of a controller. A time-varying process can require use of a real-time indirect adap tive controller, and a process with variable time delay may also call for a delay-time predictor. This paper describes a particular structure for such a controller and demonstrates its application to a pulp bleaching process. The variable delay time predictor constitutes the novel contribution of theis work. We discuss aspects of controlling the pulp bleach ing process at Irving Paper Ltd., which is an extension on the work done in Sayda and Taylor [1]. The bleach ing process was thoroughly studied, and single-input single-output process models identified on-line. This investigation showed that the process was accurately modeled as a first-order system plus a variable delay time. This is a difficult process to control, since the delay time varies substantially with pulp flow into and out of the bleaching vessel. The efficacy and robust ness of our new technique is demonstrated by control ling the pulp bleaching process using an indirect adap tive model predictive control algorithm with a recur sive least squares identifier and a variable delay time predictor embedded in that controller.

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