Type: Conference Paper
An adaptive PID tuning for LFC system using neuro-fuzzy inference system
Journal: ()Year: 2019/01/01Volume: Issue: Pages: 155 - 160
Language: English
Abstract
A new control scheme, based on Artificial Neuro-Fuzzy Inference System (ANFIS) is used to design a robust Proportional Integral Derivative (PID) controller for Load Frequency Control (LFC). The controller algorithm is trained by the results of off-line studies obtained by using particle swarm optimization. The controller gains are optimized and updated in real-time according to load and parameters variations. Simulation results of this method on a multi-machine system in comparison with conventional fuzzy controller show the satisfactory results, especially where the parameters of the system change. © 2019 ICAI 2015 - WORLDCOMP 2015. All rights reserved.
Author Keywords
Fuzzy ControlLoad Frequency ControlParticle Swarm OptimizationPID ControllerArtificial intelligenceControllersElectric control equipmentElectric load managementFuzzy controlFuzzy inferenceFuzzy systemsParticle swarm optimization (PSO)Press load controlProportional control systemsThree term control systemsTwo term control systems
Other Keywords
Artificial intelligenceControllersElectric control equipmentElectric load managementFuzzy controlFuzzy inferenceFuzzy systemsParticle swarm optimization (PSO)Press load controlProportional control systemsThree term control systemsTwo term control systemsController algorithmConventional fuzzy controllersLoad-frequency controlMultimachine systemsNeuro-fuzzy inference systemsParameters variationsPID controllersProportional integral derivative controllersElectric frequency control