Dursun E.H.2024-12-102024-12-102024979-833153149-2https://doi.org/10.1109/IDAP64064.2024.10710696https://hdl.handle.net/20.500.13091/96738th International Artificial Intelligence and Data Processing Symposium, IDAP 2024 -- 21 September 2024 through 22 September 2024 -- Malatya -- 203423This study presents the implementation of two distinct controller designs, optimized with particle swarm optimization (PSO), for the conventional automatic voltage regulator system (AVR). These designs are proportional integral derivative (PID) controller without filter, which is known as ideal in the literature, and PID-F controller with filter. This study aims to identify the optimal parameters of controllers by employing the PSO algorithm. While a variety of objective functions are considered in the study, a current objective function, ZLG+ITAE, which represents a combination of Zwe-Lee Gaing (ZLG) and the integral-time absolute error (ITAE) objectives, is also employed in the tests. Thus, five different controllers are developed for the objective functions used. The study is initially modeled in a simulation environment with known standard AVR system parametric data. A comparison of the obtained performance data reveals that the GLZ+ITAE objective function yields more successful results. The system is evaluated both transiently and in steady state, according to specific criteria. The results demonstrate that more optimal dynamic response can be achieved. Furthermore, the comprehensive results illustrate that the four-parameter PID-F controller structure optimized via PSO can yield improved outcomes compared to those of the ideal PID. © 2024 IEEE.eninfo:eu-repo/semantics/closedAccessAVR systemfiltered PID-F controllerideal PID controlleroptimal control system designPSO optimizationDynamic responseIntegrated circuit designInvarianceOptimal control systemsProportional control systemsStructural dynamicsThree term control systemsTwo term control systemsAutomatic voltage regulator system systemAutomatic voltage regulator systemsControl system designsFiltered proportional integral derivative-F controllerIdeal proportional integral derivative controllerOptimal control system designOptimal controlsOptimisationsParticle swarmParticle swarm optimization optimizationProportional integral derivativesProportional-integral-derivatives controllersSwarm optimizationParticle swarm optimization (PSO)Conference Object10.1109/IDAP64064.2024.107106962-s2.0-85207950578