A multituning fuzzy control system structure that involves two simple, but
effective tuning mechanisms, is proposed: one is called fuzzy control rule
tuning mechanism (FCRTM); the other is called dynamic scalar tuning mechani
sm (DSTM). In FCRTM, it is used to generate the necessary control rules wit
h a center extension method. In DSTM, it contains three fuzzy IF-THEN rules
for determining the appropriate scaling factors for the fuzzy control syst
em. In this paper, a method based on the genetic algorithm (GA) is proposed
to simultaneously choose the appropriate parameters in FCRTM and DSTM. Tha
t is, the proposed GA-based method can automatically generate the required
rule base of fuzzy controller and efficiently determine the appropriate map
For building the dynamic scalars of fuzzy controller. A multiobjective fit
ness function is proposed to determine an appropriate parameter set such th
at not only the selected fuzzy control structure has fewer fuzzy rules, but
also the controlled system has a good control performance. Finally, an inv
erted pendulum control problem is given to illustrate the effectiveness of
the proposed control scheme.