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The results demonstrated that the controller has generated substrate and air flow rates as an output acceptable in large scale.
It will be demonstrated that the controller design for EMC load cells can be based on the derived parameters.
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The result obtained with the uncertain RGA demonstrates that the controller pairings suggested by nominal RGA can lead to control configurations with loops that may become unstable.
The simulation results demonstrate that the controller stabilizes the system.
The simulation results demonstrate that the controller may improve transient stability and dynamic performance of power systems significantly.
With the two on-line methods, we demonstrate that the controller can learn through interaction with its environment to overcome simulated failure of its sensors.
By implementing the controller and observer on the system, simulations demonstrate that the controller lead to reduction of the tether libration from large amplitudes.
The designed controller and observer are implemented to the nonlinear plant and simulations demonstrate that the controller lead to reduction of the tether libration propoerly.
Most importantly for our purpose, we demonstrate that, as the controller's equity stake declines, the expected governance costs increase and, furthermore, the expected costs go up at an increasing rate.
Then, it is formally demonstrated that the proposed controller actually meets the desired control objectives.
Simulation results demonstrated that the proposed controller performed better in comparison to the nonlinear inversion-based control method and an advanced neural network-based hybrid controller.
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Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com