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Optimal Operation for Reduced Energy Consumption of an Air Conditioning System Using Neural Inverse Optimal Control
2022
Mathematics
For a comfortable thermal environment, the main parameters are indoor air humidity and temperature. These parameters are strongly coupled, causing the need to search for multivariable control alternatives that allow efficient results. Therefore, in order to control both the indoor air humidity and temperature for direct expansion (DX) air conditioning (A/C) systems, different controllers have been designed. In this paper, a discrete-time neural inverse optimal control scheme for trajectories
doi:10.3390/math10050695
fatcat:eby7ohe6srbbbfke63ub5ku4vi