부산대학교 도서관

Multi-parametric programming is a mathematical theory to address optimization problems involving varying parameters. This thesis is concerned with the development of model-based controllers via parametric programming and their application to the design, operation and control of process systems. In part I of this thesis two new algorithms are presented for solving parametric optimization problem of linear state space models via dynamic programming. The first algorithm solves the nominal case, while the second introduce the case of uncertainty in the system matrices. Moreover, an algorithm for robust Explicit model based controller for box-constrained linear systems. These algorithms constitute the basis for the development of model based controllers in the rest of the thesis. In part II of this thesis, dynamic mathematical models for the cases of metal hydride tank reactor, Proton Exchange Membrane (PEM) fuel cell unit and tunnel kiln process are presented. These mathematical models are used to derive reduced order linear models in order to design explicit/multi-parametric Model Predictive Controllers. Moreover, the extensive design of an experimental PEM fuel cell unit which includes the process and instrumentation diagram (PID), the complete list of materials and the three dimension design of the unit, is presented. Based on the experimental results provided by the manufacturer, a validated dynamic mathematical model of the PEM fuel cell unit is presented. Finally, mathematical modelling, dynamic optimization and design of PI controller for the firing process of a tunnel kiln is presented.