Model-free control based on reinforcement learning for a wastewater treatment problem
Applied Soft Computing
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Wastewater from textile industries is not satisfactorily depolluted by conventional wastewater treatments because of their refractory composition. The use of Advanced Oxidation Processes (AOPs) has shown to be very effective to degrade this type of wastewater. Fenton's reaction is one of the AOPs commonly applied for removing of refractory dyes. Due to the complex mechanism of Fenton's reaction, very few theoretical models representing the process kinetics have been developed. This paper proposes a theoretical model for the degradation of Methylorange (MO) by Fenton reagent, which involves the initial concentrations of the reagents (hydrogen peroxide and ferrous sulfate) and approximates experimental data in the steady state. Also, a study is conducted on the variables affecting the process (i.e. temperature, pH, reagents and MO concentrations) to set appropriate operational conditions to carry out the reaction efficiently.