Open AccessSliding Mode Self-Tuned Single Neuron PID Controller for Power System Stabilizer
Author(s) -
M. A. Abdel Ghany,
Mohamed Α. Shamseldin
Publication year - 2021
Publication title -
wseas transactions on computers
Language(s) - English
Resource type - Journals
eISSN - 2224-2872
pISSN - 1109-2750
DOI - 10.37394/23205.2021.20.34
Subject(s) - control theory (sociology) , pid controller , controller (irrigation) , stabilizer (aeronautics) , electric power system , computer science , power (physics) , mode (computer interface) , control engineering , engineering , control (management) , temperature control , physics , mechanical engineering , agronomy , quantum mechanics , artificial intelligence , biology , operating system
In this paper, a modified technique based on the combination of the Single Neuron PID (SNPID), as the main controller and Sliding Mode Control (SMC), as an adaptation technique, to design an optimized self-tuned for SNPID controller that may overcome difficulties faced when a change in system operating points occurs. The proposed approach has been implemented as a power system stabilizer (PSS) for a synchronous generator connected to an infinite bus. The Flower Pollination (FP) optimization is based on an appropriate objective function. To demonstrate the effectiveness of the combination obtained controllers, PSS, is tested under different operating conditions. The combination controllers are shown through uncertainties system parameters changes under different disturbances. The results show the ability of the suggested controllers to enhance well the system performances