Improving the Performance of Uncertain Disturbed Two Population Microbial Fuel Cell Using Robust Adaptive Sliding Mode Control.

This article presents a new control approach for the optimal and reliable operation of the microbial fuel cell, as one of the most important sources of renewable energy. Considering several adverse effects on the performance of the microbial fuel cell, including the effects of uncertainty, disturbance, and of course, taking into account the nonlinear dynamics and the necessary conditions for the stable and optimal operation of the fuel cell, this paper presents a novel robust hybrid approach to its performance management. The innovative approach by using adaptive and sliding mode techniques, by focusing on providing a theoretical solution and not changing the structure of the fuel cell, reduces and suppresses the effects of disturbance and uncertainty of the model, and by guaranteeing the stable and reliable operation of the microbial fuel cell in the Lyapunov concept, provides rapid regulation of system states. The results of simulation and comparison in the MATLAB environment show the efficiency and optimal performance of the fuel cell system under the planned control method from the perspective of improving the transient and permanent response. [ABSTRACT FROM AUTHOR]