TITLE:
Adaptive Fuzzy Sliding Mode Controller for Grid Interface Ocean Wave Energy Conversion
AUTHORS:
Adel A. A. Elgammal
KEYWORDS:
Grid integration, Wave Energy Conversion Systems, Self-Excited Induction Generator (SEIG), Vector Control, Genetic Algorithm (GA), Particle Swarm Optimization (PSO), Sliding Mode Control (SMC), Fuzzy Logic Control (FLC), Membership Function Tuning
JOURNAL NAME:
Journal of Intelligent Learning Systems and Applications,
Vol.6 No.2,
May
2,
2014
ABSTRACT:
This paper presents
a closed-loop vector control structure based on adaptive Fuzzy Logic Sliding
Mode Controller (FL-SMC) for a grid-connected Wave Energy Conversion System (WECS)
driven Self-Excited Induction Generator (SEIG). The aim of the developed
control method is to automatically
tune and optimize the scaling factors and the membership functions of the Fuzzy
Logic Controllers (FLC) using Multi-Objective Genetic Algorithms (MOGA) and
Multi-Objective Particle Swarm Optimization (MOPSO). Two Pulse Width Modulated
voltage source PWM converters with a carrier-based Sinusoidal PWM modulation
for both Generator- and Grid-side converters have been connected back to back between
the generator terminals and utility grid via common DC link. The indirect vector control scheme is
implemented to maintain balance between generated power and power supplied to
the grid and maintain the terminal
voltage of the generator and the DC bus voltage constant for variable rotor
speed and load. Simulation study has
been carried out using the MATLAB/Simulink environment to verify the
robustness of the power electronics converters and the effectiveness of
proposed control method under steady state and transient conditions and also
machine parameters mismatches. The
proposed control scheme has improved the voltage regulation and the
transient performance of the wave energy scheme over a wide range of operating
conditions.