A complex and demanding task in control theory is the optimization
of the behaviour of systems. But what does optimal mean? Roughly
spoken it means that one tries to find the "best" solution of an
existing problem, for example to maximize the acceleration of a car
or to minimize the energy consumption of a plant. The search for a
control that fulfills necessary constraints while maximizing (or
minimizing) the desired objective defines - according to the
fundamental problem of optimization theory in the field of dynamic
systems. If there are uncertainties that act upon the system which
has to be controlled, it is necessary to make decisions without
knowing what the e.ects might be in detail. The contribution of
this book shall be to present algorithms that are able to imprint a
desired optimal behavior onto a system - despite of occurring
uncertainties - while the algorithms itself shall remain
practically implementable. This means that the effort (necessary
hardware, time needed to obtain the desired solution) has to stay
within reasonable limits - which are given by the respective task
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