State and disturbance observer-based predictive control for DC–DC converters integrated with a photovoltaic system

The article introduces a state and disturbance observer-based predictive control system for DC–DC converters integrated with photovoltaic systems. It addresses the challenge of regulating the output voltage of PV-integrated DC–DC converters, particularly the photovoltaic integrated DC–DC Buck Converter (PVBC). The authors propose a discrete-time integral sliding mode observer (DISMO) to estimate inductor current and perturbations in PV panel voltage, eliminating the need for expensive sensors. The DISMO design includes mathematical proofs for error convergence and stability. The article also implements predictive control using the estimates from DISMO, demonstrating superior performance over traditional PI controllers in various scenarios, such as step and ramp variations in irradiation, temperature, and load. The simulation results highlight the effectiveness of the proposed DISMO-based predictive controller in maintaining stable output voltage with minimal transient and steady-state errors. This work paves the way for future cost-effective controllers in MPPT applications.