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This paper discusses an optimal control approach to the life cycle optimization of water-flooding problem by calculating the optimal switching times given the optimal wells settings to be bang bang controls.
In this paper, optimal switching characteristics of a CMOS inverter are realized using an evolutionary optimization approach called differential evolution (DE) algorithm.
An analytical solution is then derived for the optimal switching times.
It is close closer to the corresponding optimal switching filter respect to other analogous hybrid method.
This paper studies the problem of optimal switching surface design for hybrid systems.
Therefore, the central component of the driver model is a framework which determines the optimal switching sequence of the movemes.
Although this method yields globally optimal switching time sequences, it is not feasible in practice due to its computational complexity.
The optimal switching times are obtained using the gradient obtained from the adjoint-based method combined with the line search algorithm.
By exploiting some particular features of the problem, the best mode sequence and the optimal switching instants are characterized analytically using a variational approach.
Our goal is to design an optimal switching control scheme to simultaneously maximize 1,3-PD productivity and 1,3-PD yield under time-delay uncertainty.
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Based on this technique, the controllability and stabilisability of such SBCNs are solved and an algorithm for finding all time-optimal switching state feedbacks is proposed.
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