OPTIMAL NEURAL FEEDBACK CONTROL FOR CARBON TAX POLICY GAUGING IN TRANSPORTATION

摘要

The effects of carbon emissions have been the objective of an investiga-tion that was based on the model of the nation-wide transportation systemwith railway, waterway, and roadway. The dynamics of such a complex phe-nomenon depends on a set of control variables (i.e., the percentage of carbontax on the fuel cost, the operational cost coverages, and growth rates of thevarious transportation modes) that can be chosen in a suitable way so asto minimize a given cost function (e.g., carbon emissions, public and privatecosts, fuel consumption, etc.). This problem has been addressed by searchingor a feedback control law that can be approximated by means of the com-bination of both Dynamic Programming and neural networks. Preliminarysimulation results with the afore-mentioned model are presented to demon-strate the effectiveness of the proposed method.