The main goal of this paper is to control the speed of a separately excited DC motor (SEDM)
with a new proposed fuzzy neural (FN) controller. This proposed method is used to adjust
the fractional order proportional integral derivative (FOPID) parameters of the controller. Also
the proposed control diagram solves the problem of parameter setting of the FN controller
more effectively with use of particle swarm optimization (PSO) algorithm. In simulation with
MATLAB 2017b, 250 series of data were used: 175 series of data, equivalent to 70% for …

The dynamic behavior of a PID-type fuzzy logic control depends on the appropriate choice of
its scaling factors. Fixed scaling factors cannot provide adequate control performance under
a wide range of operating conditions. This paper proposes a control strategy for separately
excited dc motor (SEDCM) speed control based on fuzzy logic and neural networks. The
function of the neural networks is to adapt the scaling factors at the inputs and output of the
fuzzy logic controller. Using MATLAB/Simulink, the performance of the proposed controller is …