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Mathematically, the objective is defined as a stochastic criterion, belonging to the class of linear quadratic regulator (LQR) optimal control problems.
In this paper, based on the LQR approach, a new optimal control structure is proposed, which optimizes the combined stochastic criterion that includes the identification of the optimal coefficient for adjusting the given trade-off.
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The spatial distribution of pits formed on a stainless steel electrode is analysed by means of two stochastic criteria based on the Poisson distribution law.
The first procedure compares systems over the quantile set of interest by a first-order stochastic dominance criterion.
A new delay-dependent stochastic stability criterion on the stochastic stability of the system is derived based on a novel Lyapunov Krasovskii functional (LKF) approach.
The systems that are deemed nondominant in the first procedure could be compared by a weaker almost first-order stochastic dominance criterion in the second procedure.
Furthermore, a stochastic stability criterion is established for all admissible uncertainties, which can guarantee the error system and sliding mode dynamics to be asymptotically stochastic stable with a given disturbance attenuation level.
Thirdly, an asymptotically stochastic stability criterion is established by utilizing a new-type Lyapunov function to guarantee the error system and sliding mode dynamics to be asymptotically stochastic stable with a given disturbance attenuation level.
This paper proposes an innovative framework for solving stochastic multi-criteria decision making (MCDM) problems when uncertainties exist in criteria performance values (PVs) and criteria weights (CWs) simultaneously.
Algorithm 3.1 (Interactive Algorithm for Stochastic Bi-criteria Problems).
So, Problem (1.1) is a stochastic bi-criteria optimization problem.
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CEO of Professional Science Editing for Scientists @ prosciediting.com