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SET induced COMParison principles for COMPlex syst.. (SetComp)
SET induced COMParison principles for COMPlex systems
(SetComp)
Date du début: 1 juil. 2012,
Date de fin: 30 juin 2014
PROJET
TERMINÉ
The current trend in control engineering which is traditionally defined by the societal needs is to deal with the complexity of dynamical systems in order to provide tools that allow the development of efficient, sustainable and low-cost solutions to control problems. Systems developed by engineers are now large-scaled, networked, and exhibit high nonlinear behavior. Also, the efficient development of reseasrch fields such as systems biology is increasingly allowing the exact study of natural phenomena, slowly moving away from a reductionism philosophy. The research agenda concerns the stability analysis and contrtol synthesis by enhancing an already advanced theoretical tool stemming from Lyapunov stability theory, which is Comparison systems theory. The introduction of new original concepts such as Dual Comparison principle and Control Comparison systems, along with the generalization and relaxation of the theory in order to provide viable solutions will bridge the gap between theory and practice in control engineering.Complex systems cannot be controlled with simplistic techniques. The proposed method does not simplify or approximate, rather, it aims at exploiting the structure of the complex dynamics. These new ideas and techniques will be implemented in crucial real life systems, namely energy conversion, water management, and systems biology. In detail, the method will be applied to switched power converters aiming at reducing energy consumption as well as improving energy conversion. The method will be applied to the activated sludge process in order to lead to more reliable performance guarantees for wastewater treatment. Lastly, the introduction of set-theoretic approaches stemming from the comparison principle in population dynamics in biology is unique and the possible implications will provide a new insight on the complexity structure.The qualities of the researcher and the ideal environment provide a strong guarantee these goals will be reached.
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