Artificial intelligence based nonlinear control of hybrid DC microgrid for dynamic stability and bidirectional power flow

Robust Cascade MRAC for a Hybrid Grid-Connected Renewable Energy System

“…Moreover, the manuscript shows simulation results as in [15][16][17]22,23]. These show the proposal ensures robustness in front of the plant s time-varying parameter changes, in contrast to [29,30,32]. Finally, the paper has the following specific novelties:…”

“…Moreover [28], employs a nonadaptive backstepping nonlinear controller, assuming all parameters are known. The works [29,30] propose nonadaptive sliding mode controllers (SMC). Here [29], details how the power and current injection versus the voltage of photovoltage panels (PVP) depend on their characteristics curves depending on the irradiance and temperature changes.…”

“…Then, the designed SMC ensures robustness despite these variations. On the other hand, the SMC from [30] works for a more extensive system, considering batteries, wind turbines, and fuel cells (FC). All these studies [28][29][30] have a complete theoretical analysis, again for non-grid-connected renewable systems.…”

“…On the other hand, the SMC from [30] works for a more extensive system, considering batteries, wind turbines, and fuel cells (FC). All these studies [28][29][30] have a complete theoretical analysis, again for non-grid-connected renewable systems. These describe the dynamical model, controller design, and stability proof.…”

“…The DC and AC subsystems are interconnected and dynamically coupled, as detailed in [31] (Chapter 8). The work [32] considers this DC/AC coupling effect and proposes adaptive SMC instead of the nonadaptive SMC from [29,30]. As a result, it improves robustness under parameter variations.…”