With the sustained development of human being, the requirement of energy, especially clean energy, becomes more and more emergent. Hydrogen energy, as a new clean energy, draws great attention around the world in recent years. The PEM (Proton exchange membrane) fuel cell as one of the applications of hydrogen energy has become a key research area because of its clean, quiet, efficiency and low start temperature, etc. Different kinds of fuel cell units, which elevate the requirement of controller design, have been developed through several years of hard working. This dissertation proposed several advanced control methods for the 1kw hydrogen-air proton exchange membrane fuel cell system developed by the Institute of Automation of the Chinese Academy of Sciences.The main contributions of this dissertation include the following: （1）The control of proton exchange membrane fuel cells has been studied with no current feedback of the load. Considering the linear control method, this dissertation has proposed a singular pencil model based adaptive state feedback predictive control method. Due to the complicated nonlinear time-vary essence of the fuel cell process, as for nonlinear control method, this dissertation has also proposed a real-time simplified variable domain fuzzy control method to further improve the control performance, which can realize both the real-time control and the accurate control at the same time. （2）The control of proton exchange membrane fuel cell has been investigated with current feedback of the load. This dissertation has implemented the fuzzy control based on the dynamically connected SIRMs fuzzy inference model and realized the control of two controlled outputs (i.e., the cathode pressure and air flow) using one manipulated variable (i.e., the set voltage of the air mass flow meter) for the first time. Furthermore, this dissertation has first developed the C-S based on-line random search optimization method to optimize the dynamic importance degree (DID) of the fuzzy logic model.（3）Power regulating method of the fuel cell and the ultra-capacitor hybrid power system has been studied. Combination of the fuel cell and the ultra-capacitor can meet the different power requirements of the load. This has been illustrated by simulation. （4）A networked control method of the fuel cell has been developed. This dissertation has proposed a novel networked predictive fuzzy control method based on a linear or nonlinear predictive model. The phenomenon of time-delay and data loss can be overcome through model prediction, fuzzy controller design and delay compensation. In a word, this dissertation has studied several new, simple and practical control methods for proton exchange membrane fuel cells and made many fruitful attempts and significant progresses for the hybrid power system which consists of fuel cell and ultra-capacitor.
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