Abstract
Industries have many rotational operations that are used for design, transport, lift, drilling, rolling, robotics, and many other applications. These rotating applications require a proper controller for accurate control of the operation. Separately excited DC motors (SEDCMs) are versatile and have various industrial operations because of their specific speed control characteristics. So, for smooth and accurate operation of an SEDC motor, controllers should be used. PI and PID controllers are used in many cases, but they are ineffective for nonlinear load operation. A fuzzy controller is a heuristic controller and can provide automatic control of the operation. Its operation depends on the selection of the correct membership values. This work proposes a novel particle swarm optimization (PSO) technique that would provide the optimum value of the membership for fuzzy controllers for optimum control of the industrial processes. To obtain SEDC results, MATLAB simulation was performed, and the fuzzy controller with novel PSO was implemented. A fuzzy PSO controller used for motor speed control operation obtains a rise time of 0.00026 s, settling time of 0.000214 s, maximum overshoot of zero, and delay time of 0.016 s, which are the best values when compared to PID and PID-Fuzzy controllers. It is observed that the results obtained from the separately excited DC motor using a fuzzy PSO controller improve the dynamic behavior of the motor that so it smoothly tracks the required speed without any more overshoot or oscillation than the PID controller. Such dynamic, stable operation of the motor makes it perfect for industrial as well as household operations.
Funder
Technical University of Ostrava
Subject
Electrical and Electronic Engineering,Computer Networks and Communications,Hardware and Architecture,Signal Processing,Control and Systems Engineering
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