Logic-Based Modeling and Optimization of Discrete-Continuous Dynamic Systems
The economic performance of chemical process systems can be significantly improved using process modeling, simulation and optimization. For transient chemical process systems or continuous processes in transient phases, dynamic models are required that are capable to predict the process behavior in a wide range of operating conditions. In addition to the transient nature, many processes exhibit discontinuities triggered by discrete events. The corresponding process models combine elements from both discrete and continuous dynamics to result in discrete-continuous dynamic models. In this thesis, a logic-based modeling and optimization method for the synthesis of such processes is proposed. By capturing the discrete and the continuous elements in a structured way, the proposed logic-based modeling method leads to optimization models that can be solved very robustly and efficiently using tailored optimization techniques. This is illustrated using applications from two different areas: hybrid optimal control and the design of complex batch distillation processes.