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Money, she argues, drives the system; the chase to garner funds distorts priorities and fragments services.
A non-linear, model-based controller asymptotically drives the system energy to zero.
It has been shown that software controller successfully drives the system through DSP board, thus enabling an accurate position control.
The construct drives the system to look for things to be wrong — a search that will be successful in most of us.
The series of designed controllers drives the system states from starting point to the desired state through a series of connected polytopic regions.
On the lower level a supersaturation control approach is used that drives the system in the phase diagram according to a concentration versus temperature trajectory.
In practical applications of feedback control, time delay arises frequently and can severely degrade closed-loop system performance and in some cases, drives the system to instability.
In the same hybrid self-triggered framework, we also design a time-varying controller which asymptotically drives the system to consensus.
Simulation results indicate that the proposed switching control law drives the system state trajectories onto the chosen switching surface in finite time and the output tracking is achieved.
Next, a controller is derived which successfully drives the system from any given initial state in the initial set to the target set while minimizing a cost function.
An adaptive learning technique is introduced to construct an optimum seeking algorithm that drives the system states to optimal equilibrium concentrations of the reaction mixture.
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Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com