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Whilst the design process suggested the controller was stable, the control input was also variably attenuated for additional safety.
The H∞ controller was stable with certain parameter uncertainties and it was not sensitive to the LC resonance frequency.
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The results of hardware-in-the-loop testing show that the control strategy works and that the controller is stable.
The data-driven control optimisation problem is constrained by NI properties to guarantee that the controller is stable and identifiable.
The resulting controller is stable and shows good performance.
The diode laser controller is stable within +/−8 μA and +/−10 mK, respectively.
We give sufficient conditions for the synthesis of the observer gain and of the state feedback controller gain separately and we show that the closed-loop system obtained with the observer based controller is stable.
It is proved that the controller is stable despite the difference between the time shifted preview measurements (expected wind speed) and actual wind speed measured at the turbine site.
It ensures that the closed-loop systems have good robustness and the controllers are stable.
To overcome this problem, we propose to employ the Lyapunov Exponent in order to determine whether fuzzy controllers are stable.
The proposed technique searches for a norm constrained stable transfer matrix Q in the H∞ and H2 suboptimal controller parameterizations so that the final controllers are stable.
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Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com