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The proposed control strategy is based on a second-order sliding manifold MIMO approach, that is used to design a robust multivariable linear controller.
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An iterative data-driven correlation-based method has been proposed recently to tune multivariable linear time-invariant controllers in closed-loop operation.
The purpose of this paper is to present a multivariable linear parameter varying (LPV) controller with a gain scheduling Smith Predictor (SP) scheme applicable to open-flow canal systems.
In this work, a methodology for a controller design of multivariable linear time invariant systems is presented.
The linear model is multivariable linear regression.
Step-wise descending multivariable linear and logistic regression were performed.
Data were analyzed using a multivariable linear mixed regression model.
Results of the multivariable linear regression model examining annual mandibular growth are summarized in Table 1.
Multivariable linear regression showed no other significant characteristics associated with the CarerQoL-7D score.
The multivariable linear regression models were fit using the ordinary least squares method.
Factors associated with base excess were identified using a multivariable linear regression.
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