Neural network-based adaptive global sliding mode MPPT controller design for stand-alone photovoltaic systems

• Published in: PloS one Vol. 17; no. 1; p. e0260480
• Main Authors: Haq, Izhar Ul, Khan, Qudrat, Ullah, Safeer, Khan, Shahid Ahmed, Akmeliawati, Rini, Khan, Mehmood Ashraf, Iqbal, Jamshed
• Format: Journal Article
• Language: English
• Published: United States Public Library of Science 20.01.2022; Public Library of Science (PLoS)
• Subjects: Algorithms; Alternative energy sources; Biology and Life Sciences; Computer and Information Sciences; Computer engineering; Computer Simulation; Control equipment; Control systems design; Controllers; Converters; Electric Power Supplies; Energy demand; Engineering and Technology; Environmental changes; Environmental conditions; Environmental pollution; Equipment Design; Harmonic distortion; Maximum power tracking; Neural networks; Neural Networks, Computer; Nonlinear control; Photovoltaic cells; Photovoltaics; Pollution control; Product development; Renewable Energy; Research and Analysis Methods; Sliding mode control; Solar Energy; Sunlight; Tracking control; United Kingdom; Islamabad Pakistan; Pakistan
• ISSN: 1932-6203; 1932-6203
• DOI: 10.1371/journal.pone.0260480

The increasing energy demand and the target to reduce environmental pollution make it essential to use efficient and environment-friendly renewable energy systems. One of these systems is the Photovoltaic (PV) system which generates energy subject to variation in environmental conditions such as temperature and solar radiations. In the presence of these variations, it is necessary to extract the maximum power via the maximum power point tracking (MPPT) controller. This paper presents a nonlinear generalized global sliding mode controller (GGSMC) to harvest maximum power from a PV array using a DC-DC buck-boost converter. A feed-forward neural network (FFNN) is used to provide a reference voltage. A GGSMC is designed to track the FFNN generated reference subject to varying temperature and sunlight. The proposed control strategy, along with a modified sliding mode control, eliminates the reaching phase so that the sliding mode exists throughout the time. The system response observes no chattering and harmonic distortions. Finally, the simulation results using MATLAB/Simulink environment demonstrate the effectiveness, accuracy, and rapid tracking of the proposed control strategy. The results are compared with standard results of the nonlinear backstepping controller under abrupt changes in environmental conditions for further validation.