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With the identified model a controller is designed using the tools of robust control, where the objective is that the level of glucose in diabetic patient tracks the level of glucose in a healthy subject while the hypoglycemic scenarios are reduced.
It is shown that for this model a controller with excellent robustness and performance properties can be designed.
Based on the resulting mathematical model, a controller Put foam level stabilisation is designed and applied to a water model, representing the LD converter process.
Based on the resulting mathematical model, a controller for foam level stabilisation is designed and applied to a water model, representing the LD converter process.
Based on the simplified dynamic model, a controller is then presented that handles the physical human-robot interaction and that provides the operator with an intuitive direct control of the payload.
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Given the equivalent models, a controller is then designed to satisfy a priori specified tracking and stability specifications.
Employing the obtained dynamical, frictional, and wear models, a controller design method is developed to meet the objectives and satisfy the constraints.
Then, phase Takagi-Sugeno (T-S) model as a controller is provided for the mentioned system.
The drone costs $415 for a model without a controller and $455 with controller.
Then, on the basis of this model, a neural controller is developed in order to control the supercapacitor voltage.
Based on this model, a balancing controller is designed using robust predictive control techniques.
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Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com