Particle Swarm Optimization and Genetic Algorithms for PID Controller Tuning

This article compares the tuning of an inverted pendulum's proportional-integral-derivative (PID) parameters using heuristic approaches. This study intends to develop an inverted pendulum model with parameters that are based on real-world conditions. The adjustment of the pendulum's PID pa...

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Bibliographic Details
Main Authors: Mishra, Debani Prasad, Raut, Usharani, Gaur, Anubhav Prakash, Swain, Sriram, Chauhan, Suraj
Format: Conference Proceeding
Language:English
Subjects:
and GAPSO are some of the terms used
Costs
Genetic algorithm(GA)
Particle swarm optimization
Particle swarm optimization (PSO)
PD control
proportional-integral-derivative (PID) tuning
Sociology
Statistics
Time factors
Tuning
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Summary:This article compares the tuning of an inverted pendulum's proportional-integral-derivative (PID) parameters using heuristic approaches. This study intends to develop an inverted pendulum model with parameters that are based on real-world conditions. The adjustment of the pendulum's PID parameters is subsequently turned into an optimization issue. Particle swarm optimization. genetic algorithms. and a mix of the two are used to overcome this issue. After simulation in the Simulink and MATLAB environments, the success of the suggested PID tuning procedures is finally confirmed by performance indices. To get the most out of the article time response analysis is done using parameters such as max. overshoot, settling time, peak time, etc.
ISSN:2832-3017
DOI:10.1109/ICSSIT55814.2023.10060892