In this work, steady-state models were developed to describe an experimental methanol fuel processor which is intended to provide hydrogen for a fuel cell system for power generation (1.5kW). The system is consists of seven units: ATR, de-oxygenation, SR, HTS, and three PROX reactors. A systematic procedure is developed to adjust the reactor model parameters such that reasonable description of steady-state behavior. Based on the fuel processor model, optimization problems were formulated to minimize the fuel processor volume while maintaining the hydrogen flow rate and CO concentration constraint. The optimization procedure is carried out sequentially and the design variables studied include: reactor temperature, reaction chemistries. The results show that 29.2% volume reduction can be obtained. The second phase of this work studies the dynamic modeling and control of the fuel processor. A dynamic model is constructed and then the reactor model parameters were adjusted to match the temperature and composition responses. Based on the work of Lin et al. (2005), the on-demand control structure is explored here. Depending on the sensors availability (temperature, % level and ppm level CO concentration), four different control structures were evaluated. Two different types of controllers (P and PI controllers) were also investigated. The results show that the control structure with simplest instrumentation (temperature control) and simplest type of controller (P-only control) gives acceptable performance for 15%, 30%, and 50% turndown ratios. Finally, the effects of catalyst deactivation were explored. The results show that the temperature control can handle losses of catalyst activities (down to 75%) in ATR and SR. However, a 25% degradation in the HTS catalyst activity results in uncontrollable CO concentration at the PROX outlet. This may be a potential problem for a fuel process with long-term application.