Design of global climate control based on fuzzy systems with concept of carbon emissions

PLOS One Design of global climate control based on fuzzy systems Fig 18. The Global climate model’s outcome for internal temperature differ. https://doi.org/10.1371/journal.pone.0333846.g018 (seen as noise in Fig 18) in order to increase prediction accuracy. The dynamic model exhibits a significant association with measured data and accurately forecasts the greenhouse’s outside temperature. Sharp temperature swings, however, imply that the model’s performance might be further enhanced by addressing environmental variability or reducing noise. 6.2 The control cost function u(t) = 𝜓(z(t)) As a control objective, [36] proposes a closed–loop controller that matches the fossil fuel demand to the maximum extent possible while preventing compartmental network over- flows. If there is only one output, then the formula is u(t) = 𝜓(𝜅(t)) , where 𝜓 is as follows: 𝜓 ∶ R+ ↦ R+. No restriction is placed on the notation, throughout the time as it is con- tinuously differentiable and rising gradually, and fulfils the conditions 𝜓(0) = 0 as well as lim𝜅→∞ 𝜓(𝜅) = 1. Using this freedom, the controller could be improved, e.g., by parameter- izing 𝜓 with many tunable parameters. Instead of aiming for maximal simplicity, we chose to represent the imaginary buffer with 𝜅0 = 𝜅max, its initial value. A smooth controller instal- lation was also important to us. As a result, 𝜅 ≥ 𝜅max is equal to 𝜓(𝜅) = 1 . During the time when the buffer is empty and the storage 𝜅 is full, the controller is inactive, but once the buffer

competes and the rest of the storage 𝜅 decreases, the controller becomes active. In Fig 19, the readers can observed the response of atmospheric (𝜉A) in the atmosphere, and land bio- sphere. In addition, the convergence of the control inputs at different values of 𝜓(𝜅(t)) can be observed in Fig 20. Using the mathematical form given above, we can also write the control function in the following way: 𝜓(𝜅) = { g 𝜅 ≤ 𝜅max, 1 𝜅 > 𝜅max, PLOS One https://doi.org/10.1371/journal.pone.0333846 October 14, 2025 22/ 30