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Our method includes robust inverse system (RIS) design as a special case.
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Modern control system design methods, including robust control, typically lead to controllers of high complexity.
Our proposed methods include robust open-loop system design as a special case.
The proposed control method mainly includes robust predictive current control based on Lyapunov function stability (RPCC-LFS) in the inner current loop and energy equilibrium proportional-integrator (PI) control in the outer dc-link voltage loop.
The developed theoretical framework includes robust estimation and filtering methods, as well as robust error metrics.
This type includes robust cases.
These methods (which include robust data normalization and signal calculation, combined parametric and non-parametric correlation and random cross-validation) help to avoid both biological and technical noise and provide a human gene coexpression network that shows good accuracy and coverage.
The GEE method includes the calculation of robust estimates for the standard errors of the regression coefficients that ensure consistent inference even if the chosen working correlation structure is incorrect or if the strength of the correlation between patient outcomes within the same hospital varies somewhat from patient to patient.
Simulation and experimental results show that the proposed control method has satisfactory performance, including robust tracking and a smooth transition when the load power varies in the large range.
The isoapostasy method will be applicable to more diversified organisms because, as stated above, our method includes statistics of long-distance relationship and is more robust to rearrangements and indels.
Given the potential for gene drives to alter entire wild populations and therefore ecosystems, the development of this technology must include robust safeguards and methods of control (Oye et al., 2014).
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