Speed Control of a Separately Excited DC Motor Using New Proposed Fuzzy Neural Algorithm Based on FOPID Controller

  • Gholamreza FarahaniEmail author
  • Karim Rahmani


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 training the designed neural network, and about 75 series, equivalent to 30% used to test and validate the neural network. The results show that the proposed method has a lower rise time and settling time for controlling the speed of SEDM in comparison with other methods such as Ziegler–Nichols, Cohen–Coon, PSO, genetic algorithm, artificial bee colony, artificial neural network, fuzzy logic controller and adaptive neuro-fuzzy interference system for PID and FOPID controllers.


Fuzzy neural Particle swarm optimization Adaptive neuro-fuzzy interference system controller Fractional order PID Separately excited DC motor Speed control 


Compliance with Ethical Standards

Conflict of interest

The authors declare that there is no conflict of interest.


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Copyright information

© Brazilian Society for Automatics--SBA 2019

Authors and Affiliations

  1. 1.Electrical Engineering and Information Technology InstituteIranian Research Organization for Science and Technology (IROST)TehranIran

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