Adaptive Intelligent Sliding Mode Control of a Photovoltaic Grid-Connected Inverter
Source abstract
Abstract
Adaptive intelligent sliding mode control methods are developed for a single-phase photovoltaic (PV) grid-connected transformerless system with a boost chopper and a DC-AC inverter. A maximum power point tracking (MPPT) method is implemented in the boost part in order to extract the maximum power from the PV array. A global fast terminal sliding control (GFTSMC) strategy is developed for an H-bridge inverter to make the tracking error between a grid reference voltage and the output voltage of the inverter converge to zero in a finite time. A fuzzy-neural-network (FNN) is used to estimate the system uncertainties. Intelligent methods, such as an adaptive fuzzy integral sliding controller and a fuzzy approximator, are employed to control the DC-AC inverter and approach the upper bound of the system nonlinearities, achieving reliable grid-connection, small voltage tracking error, and strong robustness to environmental variations. Simulation with a grid-connected PV inverter model is implemented to validate the effectiveness of the proposed methods.
Source: crossref · Quality: baseline
Research context
OpenAlex topics: Photovoltaic System Optimization Techniques · Microgrid Control and Optimization · Power Systems and Renewable Energy
SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.
Affiliations
College of Electrical and Mechanical Engineering, Hohai University, Changzhou 213022, China
Funding
Natural Science Foundation of Jiangsu Province
References (22)
Show source-provided references
1. A variable step size INC MPPT method for PV systems10.1109/TIE.2008.920550 ↗
2. Novel and Fast Maximum Power Point Tracking for Photovoltaic Generation
3. Efficiency optimization of a DSP-based standalone PV system using fuzzy logic and dual-MPPT control10.1109/TII.2012.2192282 ↗
4. Maximum power point tracking for PV system using advanced neural networks technique
5. Enhancement of Fuzzy Controlled Photovoltaic-Diesel System with Battery Storage Using Interleaved Converter with Hybrid MPPT for Rural Home10.1115/1.4031514 ↗
6. An improved particle swarm optimization (PSO)-based MPPT for PV with reduced steady-state oscillation10.1109/TPEL.2012.2185713 ↗
7. Robust fuzzy controlled photovoltaic power inverter with Taguchi method10.1109/TAES.2002.1039410 ↗
8. Adaptive Fractional Order Sliding Mode Controller with Neural Estimator10.1016/j.jfranklin.2018.01.006 ↗
9. A multilevel inverter for photovoltaic systems with fuzzy logic control10.1109/TIE.2010.2044119 ↗
10. Fei, J., and Wang, T. (2018). Adaptive Fuzzy-Neural-Network Based on RBFNN Control for Active Power Filter. Int. J. Mach. Learn. Cybern., 1–12.10.1109/ICA-SYMP.2019.8646315 ↗
11. Dynamic Global PID Sliding Mode Control Using RBF Neural Compensator for Three-Phase Active Power Filter10.1177/0142331217726955 ↗
12. Sliding-Mode Control of PWM Dual Inverter-Based Grid-Connected PV System: Modeling and Performance Analysis10.1109/JESTPE.2015.2497900 ↗
13. A new backstepping finite time sliding mode control of grid connected PV system using multivariable dynamic VSC model10.1016/j.ijepes.2016.03.034 ↗
14. MPPT for photovoltaic system using nonlinear backstepping controller with integral action10.1016/j.solener.2018.04.061 ↗
15. Fang, Y., Fei, J., and Yang, Y. (2018). Adaptive Backstepping Design of a Microgyroscope. Micromachines, 9.10.3390/mi9070338 ↗
16. Adaptive Backstepping Fuzzy Sliding Mode Vibration Control of Flexible Structure
17. Achievement of MPPT by finite time convergence sliding mode control for photovoltaic pumping system10.1016/j.solener.2018.03.026 ↗
18. Backstepping based non-linear control for maximum power point tracking in photovoltaic system10.1016/j.solener.2017.10.062 ↗
19. Fuzzy logic based dynamic sliding mode control of boost inverter in photovoltaic application10.1063/1.4928737 ↗
20. Disturbance Observer Based Fuzzy Sliding Mode Control of PV Grid Connected Inverter10.1109/ACCESS.2018.2825678 ↗
21. Fei, J., and Zhu, Y. (2017). Adaptive fuzzy sliding control of single-phase PV grid-connected inverter. PLoS ONE, 12.10.1371/journal.pone.0182916 ↗
22. Adaptive Global Fast Terminal Sliding Mode Control of Grid-connected Photovoltaic System Using Fuzzy Neural Network Approach10.1109/ACCESS.2017.2707668 ↗