Open AccessOptimal gain scheduling of VSC‐HVDC system sliding mode control via artificial bee colony and mine blast algorithms
Author(s) -
Ramadan Haitham S.,
Fathy Ahmed,
Becherif Mohamed
Publication year - 2018
Publication title -
iet generation, transmission and distribution
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.92
H-Index - 110
eISSN - 1751-8695
pISSN - 1751-8687
DOI - 10.1049/iet-gtd.2017.0935
Subject(s) - control theory (sociology) , robustness (evolution) , matlab , gain scheduling , computer science , sliding mode control , converters , voltage , voltage source , control engineering , engineering , nonlinear system , control system , control (management) , physics , quantum mechanics , artificial intelligence , operating system , biochemistry , chemistry , electrical engineering , gene
This study focuses on the optimal gain scheduling of the robust non‐linear sliding mode control (SMC) for the voltage source converters high‐voltage direct current (VSC‐HVDC) systems, for ensuring the desired dynamic behaviour improvement and stability enhancement. First, the development of the system steady‐state mathematical model of non‐linear character is explored in order to control the active power, the reactive power, and the DC link voltage towards their desired set point values. Their measured signals, as the outputs, are controlled via the optimal SMC‐based controllers, using their reference signals directly. Both artificial bee colony and mine blast algorithm are considered to optimally select the optimal gains of SMC controller that will minimise the steady‐state error of the obtained dynamic behaviour. Therefore, the DC voltage, the active and reactive powers can be properly maintained at their reference values. Both optimal SMC‐based techniques are compared in terms of the behavioural analysis and robustness. Using MATLAB™‐Simulink, the results significantly verify that the designed controllers based on SMC can achieve favourable tracking performance and contribute efficiently towards improving the system dynamic behaviour.