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Nowadays, intelligent control methods play an important role in the advancement of technology and the human movement towards further evolution. The development of new frameworks for power generation and distribution systems by designing a microgrid structure with economic capabilities is one of these areas of progress. Therefore, this paper introduces a new practical method for controlling the frequency of provisional microgrid and is able to cover the following issues at the same time including (1) It considers the nonlinear model of provisional microgrid which has a hybrid structure (AC and DC) in addition to renewable energy sources; (2) Introduces a method for microgrid frequency control under different operational conditions that performs based on the brain emotional learning; (3) Ensures the operation and applicability of the control method for the provisional microgrid through implementation of FPGA for the first time; (4) Confirms the robustness of the proposed method under severe load changes and generation from renewable sources. So, the effects of wind turbines and solar energy are considered in the simulation scenario and under the influence of various changes in load and system uncertainties, the robustness and efficiency of the proposed method are well demonstrated. [ABSTRACT FROM AUTHOR]

One of the promising technologies in the field of clean and renewable energy is the microbial fuel cells, which in addition to generating electrical energy from the metabolism of microorganisms, can also be used to improve the environment in wastewater treatment. In fact, this paper designs an integrated control model that in the presence of uncertainty and unknown parameters can consider the effect of input variables for two-population in a chamber. In addition to maintaining closed loop stability, it has acceptable behavior in terms of time to reach steady state and reduce system error and provide satisfactory performance in terms of output energy. Lyapunov analysis ensures system stability and system control functions are demonstrated by MATLAB / Simulink simulations. [ABSTRACT FROM AUTHOR]