Since the invention of Fuzzy logic and fuzzy control, the latter has been growing in spread
and importance in many applications and devices in many life aspects. This maybe due to
the easy use of a fuzzy control system, and for being far of math co
mplications. Even if the
plant model is unknown, a self-organizing fuzzy controller (SOFC) can improve the
response of an already exist linear control table, or even can build a control table from
scratch, by assessing current performance of the controller and adjusting the control table
accordingly. This paper provides a simple article that shows how to design and use a self organizing
fuzzy controller, through a simulation example using MATLAB & Simulink
in which a variable torque loaded DC motor speed regulation is done. The simulation
showed the ability of the controller to provide a good response and decrease speed error by
a notable amount at load torque changing times. This paper can be used as textbook
material for students or researchers interested in the field of adaptive control, especially
self-organizing fuzzy control.
One ofa car's suspension system functions is to isolate vibrations resulting from road on the driver and ensure a comfortable ride. But the design of control systems for semi-active suspension systems is difficult because of the non-linearity of the
constituent elements of these systems which make the researches related to it characterized by complexity. So in order to improve the performance of semi-active suspension systems without bearing the effort of designing a model based controller, a control system is designed using self-organizing fuzzy controller based on the principle of delay-in-penalty to control a semi-active suspension system which uses a magneto rheological damper. The controller tries to enhance system performance using the desired response as it is described in the penalty table. The fuzzy logic controller is based on two inputs namely sprung mass velocity and unsprung mass velocity. Using a quarter car model with 2 degree-of-freedom the system is modeled and simulated in MATLAB &Simulink® and the results are compared to the widely used sky-hook strategy. the simulation showed the ability of the self-organizing fuzzy controller to provide good results in minimizing sprung mass acceleration in variousroad profiles compared to sky-hookstrategy.
