The lower-level subsystem deals with the control of linear and angular volocities using a multivariable PI controller described with a full matrix.
The first level subsystem deals with the control of the linear and angular volocities using a multivariable PI controller described with a full matrix.
It has been demonstrated that the manipulated variable saturation and the nonlinear dynamic behaviour are removed when auxiliary manipulated variables, obtained by bifurcation analysis, are used in a multivariable control strategy for the reactor temperature control.
In this work, it has been demonstrated that the saturation in the manipulated variable and the complex non-linear dynamic behavior are removed when auxiliary manipulated variables, obtained by bifurcation analysis, are used in a multivariable control strategy for the reactor temperature control.
This work presents the simultaneous synthesis, design and control of an activated sludge process using a Multivariable Model-based Predictive Controller (MPC).
Using a multivariable logistic regression model which controlled for age, gender, cognitive impairment, vision impairment, dehydration, and severe illness, room transfers per patient days were associated with delirium incidence (OR: 9.69, 95 % CI (6.20 to15.16), P < 0.0001).
Results were confirmed using a multivariable Cox proportional-hazards model, controlling for variables related to length of ICU stay following pediatric cardiac surgery in a previous study [ 20], variables unbalanced after matching (P < 0.10), for the propensity score and the year of surgery.
The constrained control design is approached using a multivariable anti-wind-up strategy for strictly proper controllers.
Data were analyzed using a multivariable linear mixed regression model.
This was tested using a multivariable, general linear model (multivariable GLM).
