We use nonlinear model predictive control to procure a joint control of mobility and transmission to minimize total network communication energy use. The nonlinear optimization problem is solved numerically in a self-triggered framework, where the next control update time depends on the predicted state trajectory and the accuracy of the numerical solution. Solution accuracy must be accounted for in any circumstance where systems are run in open-loop for long stretches of time based on potentially inaccurate predictions. These triggering conditions allow us to place wireless nodes in low energy ‘idle' states for extended periods, saving over 70% of energy compared to a periodic policy where nodes consistently use energy to receive control updates.
Accuracy-awareness: A pessimistic approach to optimal control of triggered mobile communication networks / Faqir, O. J.; Kerrigan, E. C.; Gunduz, D.. - 54:6(2021), pp. 296-301. (Intervento presentato al convegno 7th IFAC Conference on Nonlinear Model Predictive Control, NMPC 2021 tenutosi a svk nel 2021) [10.1016/j.ifacol.2021.08.560].
Accuracy-awareness: A pessimistic approach to optimal control of triggered mobile communication networks
Gunduz D.
2021
Abstract
We use nonlinear model predictive control to procure a joint control of mobility and transmission to minimize total network communication energy use. The nonlinear optimization problem is solved numerically in a self-triggered framework, where the next control update time depends on the predicted state trajectory and the accuracy of the numerical solution. Solution accuracy must be accounted for in any circumstance where systems are run in open-loop for long stretches of time based on potentially inaccurate predictions. These triggering conditions allow us to place wireless nodes in low energy ‘idle' states for extended periods, saving over 70% of energy compared to a periodic policy where nodes consistently use energy to receive control updates.File | Dimensione | Formato | |
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