Adaptive Fuzzy Sliding Mode Controller for Grid Interface Ocean Wave Energy Conversion

• 作者: Adel A. A. Elgammal
• 来源期刊: 智能学习系统与应用(英文)
• 学科: 工学
• 关键词: 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
• 年，卷（期）: 2014,（2）
• 页码范围: 53-69
• 页数: 17页
• 分类号: TP1

摘要

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.