A novel robust adaptive sliding mode control using stochastic gradient descent for PEMFC power system

This study represents a comparison of novel robust adaptive sliding mode control using stochastic gradient descent (ASMCSGD) versus the super twisting algorithm (STA) for the proton exchange membrane fuel cell (PEMFC) power system. PEMFC has been constantly encountered with external disturbances such as inlet gas pressures and temperature fluctuations which a novel adaptive control law should be designed to be robust against the mentioned perturbations. The proposed ASMCSGD is based on the conventional sliding mode control (SMC), which guarantees robustness and restraining external disturbances. As is common, the main drawback of conventional SMC is the generation of a chattering phenomenon. Therefore, by using the stochastic gradient descent (SGD), a novel adaptive control law is designed. Hence, the SGD can continuously calculate the adaptive gain and then guarantee robustness besides minimizing the chattering phenomenon. The stability of the PEMFC power system for both controllers ASMCSGD and STA is demonstrated via the

Automated summary

This study compares novel robust adaptive sliding mode control (ASMCSGD) with the super twisting algorithm (STA) for the proton exchange membrane fuel cell (PEMFC) power system. The ASMCSGD is based on conventional sliding mode control (SMC) and uses stochastic gradient descent (SGD) to minimize the chattering phenomenon and ensure robustness. The stability of the PEMFC power system for both ASMCSGD and STA controllers is demonstrated.