Sentence examples for optimal control over from inspiring English sources

Recent insights into the growth and optimal control over the InAs and GaAs nanowire morphology and distinguished key physical aspects in their growth are discussed.

Since there is no need for prediction, the intensive calculations for finding the optimal control over the prediction horizon can be eliminated.

To the best of our knowledge, there is limited literature in the field of optimal control over diffusion dynamics described by epidemic modeling with time-evolving parameters [6, 7].

By the same arguments as for the initial date, this implies that (V_{t}^{hat alpha } = J_{t}left (rho _{t}^{hat alpha },hat alpha right) = w_{t}(rho _{t}^{hat alpha })), which means that (hat alpha ) is an optimal control over [t,T], once we start at time t from the initial state (rho _{t}^{hat alpha }), i.e., the time consistency of (hat alpha ).

We maintain optimal control over our nutrition when we cook and prepare food for ourselves.

That allowed an optimal control over potential technical variations.

Succinctly, the underlying features of the proposed method are as follows: a sequence of predicted optimal control values over a finite horizon, for an optimally chosen input node, is obtained using Model Predictive Control ideas; the entire resulting sequence is sent to the chosen input node; a smart actuator is used to store the predictions received and apply them accordingly.

This class of ACDs uses two neural networks to evolve an optimal control strategy over time.

This paper proposes a framework where simplified power plant operation models are coupled with gradient-based optimisation techniques to determine the optimal control strategy over multiple tidal cycles.

The recursive algorithm (16 - 18 16 - 18d to obtais the optimal control policy (over the discretized state space) for different valusedof N. toe transitiobtainbabilithes optimalMarkov models are controld as described earlier.

In nonlinear model predictive control (NMPC), a control task is approached by repeatedly solving an optimal control problem (OCP) over a receding horizon.