Certainty-Equivalence-Based Sensorless Robust Sliding Mode Control for Maximum Power Extraction of an Uncertain Photovoltaic System

Zaheer Alam, Qudrat Khan, Laiq Khan, Safeer Ullah, Syed Abdul Mannan Kirmani and Abdullah A. Algethami
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Zaheer Alam: Electrical Engineering Department, COMSATS University Islamabad, Abbottabad 22060, Pakistan
Qudrat Khan: Centre for Advanced Studies in Telecommunications (CAST), Islamabad Campus, COMSATS University Islamabad, Islamabad 45550, Pakistan
Laiq Khan: Department of Electrical and Computer Engineering, COMSATS University Islamabad, Islamabad 45550, Pakistan
Safeer Ullah: Department of Electrical and Computer Engineering, COMSATS University Islamabad, Islamabad 45550, Pakistan
Syed Abdul Mannan Kirmani: Centre for Advanced Studies in Telecommunications (CAST), Islamabad Campus, COMSATS University Islamabad, Islamabad 45550, Pakistan
Abdullah A. Algethami: Department of Engineering, Taif University, Taif 11099, Saudi Arabia

Energies, 2022, vol. 15, issue 6, 1-17

Abstract: Photovoltaic (PV) arrays and their electronic converters are subject to various environmental disturbances and component-related faults that affect their normal operations and result in a considerable energy loss. Therefore, it is ever demanding to design such closed-loop operating algorithms that tolerate faults, present acceptable performance, and avoid wear and tear in the systems. In this work, the core objective is to extract maximum power from a PV array subject to environmental disturbances and plant uncertainties. The system is considered under input channel uncertainties (i.e., faults) along with variable resistive load and charging stations. A neuro-fuzzy network (NFN)-based reference voltage is generated to extract maximum power while considering variable temperature and irradiance as inputs. Furthermore, the estimated reference is tracked by the actual PV voltage under two types of controllers: certainty-equivalence-based robust sliding mode (CERSMC) and certainty-equivalence-based robust integral sliding mode (CERISMC). These strategies benefit from improving the robustness against faults (disturbances). The proposed methods use the inductor current, which is recovered via the velocity observer and the flatness property of nonlinear systems. The system’s stability is proven in the form of very appealing theorems. These claims are validated by the simulation results, which are carried out in a MATLAB environment.

Keywords: arbitrary order sliding mode control; closed-loop stability; feed forward neural network; high gain differentiator; maximum power extraction; photovoltaic system (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2022
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