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The purpose of this thesis is to investigate an alternative control strategy for a multi-variate non-linear process in a paper machine called the headbox. The proposed solution was intended to be able to be adopted on two different headbox types, currently controlled by different concepts. The methodology was to first create black-box models of the two different systems based on measurements, at one working point. Secondly, various control strategies were investigated. A more sophisticated multi-input multi-output controller MPC, or model predictive control, and a less sophisticated one, a single-input single-output, decentralised PI-controller. With help of simulations the performances of the both strategies were tested. Finally, only the decentralised control solution was implemented and evaluated through trial runs on a pilot machine. The main issue regarding the decentralised controller was the input-ouput pairing. Since the multi-variate system had four outputs and only three inputs, analysis had to be made in order to select three of those four, to form a square system. This analysis was based on the relative gain array (RGA). The resulting performance of the decentralised controller showed stability and adequate response times, surpassing the older system and making one component obsolete through the pairing changes. The MPC controller showed even better performance during simulations and shall also be taken into account if further investigatin is possible.

The purpose of this thesis is to investigate an alternative control strategy for a multi-variate non-linear process in a paper machine called the headbox. The proposed solution was intended to be able to be adopted on two different headbox types, currently controlled by different concepts. The methodology was to first create black-box models of the two different systems based on measurements, at one working point. Secondly, various control strategies were investigated. A more sophisticated multi-input multi-output controller MPC, or model predictive control, and a less sophisticated one, a single-input single-output, decentralised PI-controller. With help of simulations the performances of the both strategies were tested. Finally, only the decentralised control solution was implemented and evaluated through trial runs on a pilot machine. The main issue regarding the decentralised controller was the input-ouput pairing. Since the multi-variate system had four outputs and only three inputs, analysis had to be made in order to select three of those four, to form a square system. This analysis was based on the relative gain array (RGA). The resulting performance of the decentralised controller showed stability and adequate response times, surpassing the older system and making one component obsolete through the pairing changes. The MPC controller showed even better performance during simulations and shall also be taken into account if further investigatin is possible.