Control, estimation and identification of chemical reaction networks with an application to combustion

Current first-principles models of complex chemistry, such as combustion reaction networks, often give inaccurate predictions of the time variation of chemical species. Moreover, the high complexity and dimensionality of these models render them impractical for real-time prediction and control of chemical network processes. These limitations have motivated us to search for an alternative paradigm that is able to both identify the correct model from the observed dynamical data and reduce complexity while preserving the underlying network structure. We want to determine at the same time:
  1. Network structure.
  2. Reaction rate constants.
  3. Initial state.
H2/O2 combustion network