The spaces of system science
This way, modern system science extended the Euclidean and Cartesian spaces of system representations applied on the basis of former registered data, and made critical process characteristics visualisable and manageable for computers. Primarily, these are processes that extend to infinity, that is to steady states, and the qualitative comparison of such processes in terms of stability and reaction to disturbances. Optimisation, i.e. the reconciliation of different aspects, and design of robust processes resistant to various changes are also supported by these new methods.
These methods highlight the critical properties of the processes, including in particular states which can potentially endanger stable operation and which can be described by the location of poles; and enable us to influence the design of these properties. Such methodological achievements are especially significant in today’s complexity of the world of systems, where relations cannot be reviewed and controlled by simple, traditional practices only through computer technology. In these procedures our initial proposition about system properties with the broadest possible scope of validity and applicability gains a new meaning.
Of the transformations used in system science, the Möbius transformation and the Hardy spaces are discussed here.