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

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Abstract

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.

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Authors and Affiliations

  1. Electrical Engineering and Information Technology Institute, Iranian Research Organization for Science and Technology (IROST), Sh. Ehsani Rad St., Enqelab St., Parsa Sq., Ahmadabad Mostoufi Rd., Azadegan Highway, Tehran, 3353136846, Iran

    Gholamreza Farahani & Karim Rahmani

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  1. Gholamreza Farahani
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Farahani, G., Rahmani, K. Speed Control of a Separately Excited DC Motor Using New Proposed Fuzzy Neural Algorithm Based on FOPID Controller. J Control Autom Electr Syst 30, 728–740 (2019). https://doi.org/10.1007/s40313-019-00485-8

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