|[zwingend]||Ralf Schoknecht, Martin Spott, Martin Riedmiller, Design of selflearning controllers using Fynesse, T. Furuhashi, S. Tano, H.A. Jacobsen (Ed.), Physica-Verlag, Nov 2000.
With the growing number and difficulty of control problems there is an increasing demand for design methods that are easy to
use. Fynesse fulfils this requirement: without knowledge
of a process model the system learns a control
policy. Optimization goals like time-optimal or energy-optimal
control as well as restrictions of allowed manipulated variables
or system states can be defined in a simple and flexible
way. Fynesse only learns on basis of success and failure
of former control interactions and, thus, learning can be carried
out directly at the real process. A priori knowledge about the
control policy as, for example, a fuzzy or linear control law
considerably improves the learning process. Moreover, the learned
policy can be interpreted as fuzzy control law which allows for
easily checking the plausibility.