Metaheuristic based optimization for tuning of PID controllers for DC motor parameters

Dc motors represent linear systems up to point of saturation. In this paper, optimized tuning of DC motors has been discussed with the help of different meta-heuristic algorithms. The model of the DC motor is basically a third-order system. Dc motors, that are used in different industrial applicatio...

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Bibliographic Details
Published in:AIP conference proceedings 2022-09, Vol.2640 (1)
Main Authors: Karmokar, Soham Roy, Pal, Neelanjan, Dasgupta, Arpan, Kolay, Anirban
Format: Article
Language:English
Subjects:
D C motors
Electric motors
Evolutionary algorithms
Evolutionary computation
Genetic algorithms
Heuristic methods
Industrial applications
Linear systems
Low speed
Machine learning
Parameters
Particle swarm optimization
Performance indices
Proportional integral derivative
Tuning
Turntables
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Summary:Dc motors represent linear systems up to point of saturation. In this paper, optimized tuning of DC motors has been discussed with the help of different meta-heuristic algorithms. The model of the DC motor is basically a third-order system. Dc motors, that are used in different industrial applications including conveyors, turntables, and other places where adjustable speed and constant or low-speed torques are required, owing to their simple configuration. They also find its application in dynamic braking and reversing applications as well. Here, in this paper Genetic Algorithm, Differential Evolution, Teaching Learning Based Optimization, Particle Swarm Optimization with different performance indices (Mean Square Error and Integral time absolute error) is compared with the standard Ziegler & Nichols method. Comparison of results using standard step parameters i.e., maximum overshoot, steady-state, rise time and peak time, etc. is being discussed.
ISSN:0094-243X
1551-7616
DOI:10.1063/5.0110195