Identification, control and optimization strategies for thermo-mechanical pulping (TMP) processes

The focus of this thesis is to develop an advanced control system for existing and to-be developed Thermo-Mechanical Pulping (TMP) refining processes. Therefore, the thesis has two parts. The first part developed two different but yet complementary closed-loop identification methods to update the models used in the low-level control layer of the current advanced control systems for TMP refiners. These newly developed identification methods are specific to closed-loop systems controlled by Model Predictive Control (MPC) techniques, and successfully tailored to the presence of the MPC. By updating the existing process models, the current advanced control systems can be operated to give better performance. However, these control systems may not be able to provide optimal performance due to process disturbances. Hence, a novel economically oriented advanced control system is developed for the existing two-stage TMP refiner processes for their optimal operation when disturbances are present. This novel technique dynamically optimizes the TMP processes as opposed to conventional two-layer methods which perform process optimization at steady-state, and has shown a potential economical benefit through reduction of total specific energy of a two-stage TMP process in a simulation study. In the second part, a novel TMP process with multi-stages of Low Consistency (LC) refining is studied for its optimal operation. The proposed Nonlinear Model Predictive Control (NMPC) technique dynamically optimizes the process and provides better performance when disturbances are present. This economically oriented NMPC (econNMPC) minimizes the total specific energy consumption of the process while respecting all the process constraints and achieving final desired pulp quality. In simulation studies, a TMP process with multiple stages of LC refining was able to save significant specific energy consumption with setpoint tracking control when disturbances are present. Moreover, further reduction of specific energy has been achieved with the developed econNMPC technique.Applied Science, Faculty ofElectrical and Computer Engineering, Department ofGraduat