Global optimization of hybrid systems

Abstract

Systems that exhibit both discrete state and continuous state dynamics are called hybrid systems. In most nontrivial cases, these two aspects of system behavior in-teract to such a significant extent that they cannot be decoupled effectively by any kind of abstraction and must be analyzed simultaneously. Hybrid system models are important in many areas of science and engineering, including flip-flops and latching relays, manufacturing systems, air-traffic management systems, controller synthesis, switched systems, chemical process systems, signaling and decision making mecha-nisms in (biological) cells, robotic systems, safety interlock systems, and embedded systems. The primary focus of this thesis is to explore deterministic methods for the global optimization of hybrid systems. While the areas of modeling, simulation and sen-sitivity analysis of hybrid systems have received much attention, there are many challenging difficulties associated with the optimization of such systems. The con-tents of this thesis represent the first steps toward deterministic global optimization of