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Helicopter Control Energy Reduction Using Moving Horizontal Tail.

Oktay T, Sal F - ScientificWorldJournal (2015)

Bottom Line: Control energy savings due to this MHT idea with respect to a conventional helicopter are calculated.Parameters of helicopter FCS and dimensions of MHT are simultaneously optimized using a stochastic optimization method, namely, simultaneous perturbation stochastic approximation (i.e., SPSA).In order to observe improvement in behaviors of classical controls closed loop analyses are done.

View Article: PubMed Central - PubMed

Affiliation: College of Aviation, Erciyes University, 38039 Kayseri, Turkey.

ABSTRACT
Helicopter moving horizontal tail (i.e., MHT) strategy is applied in order to save helicopter flight control system (i.e., FCS) energy. For this intention complex, physics-based, control-oriented nonlinear helicopter models are used. Equations of MHT are integrated into these models and they are together linearized around straight level flight condition. A specific variance constrained control strategy, namely, output variance constrained Control (i.e., OVC) is utilized for helicopter FCS. Control energy savings due to this MHT idea with respect to a conventional helicopter are calculated. Parameters of helicopter FCS and dimensions of MHT are simultaneously optimized using a stochastic optimization method, namely, simultaneous perturbation stochastic approximation (i.e., SPSA). In order to observe improvement in behaviors of classical controls closed loop analyses are done.

No MeSH data available.


Loci of flapping and lead-lagging modes.
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Related In: Results  -  Collection


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fig2: Loci of flapping and lead-lagging modes.

Mentions: The qualitative behaviors of the blade flapping and lead-lagging modes are also identical with the ones given in [43] that the blade flapping modes are much farther away from the imaginary axis with respect to the blade lead-lagging modes and the magnitude of the frequency bound for the blade flapping modes is larger than the one for the blade lead-lagging modes (see Figure 2).


Helicopter Control Energy Reduction Using Moving Horizontal Tail.

Oktay T, Sal F - ScientificWorldJournal (2015)

Loci of flapping and lead-lagging modes.
© Copyright Policy - open-access
Related In: Results  -  Collection

Show All Figures
getmorefigures.php?uid=PMC4477250&req=5

fig2: Loci of flapping and lead-lagging modes.
Mentions: The qualitative behaviors of the blade flapping and lead-lagging modes are also identical with the ones given in [43] that the blade flapping modes are much farther away from the imaginary axis with respect to the blade lead-lagging modes and the magnitude of the frequency bound for the blade flapping modes is larger than the one for the blade lead-lagging modes (see Figure 2).

Bottom Line: Control energy savings due to this MHT idea with respect to a conventional helicopter are calculated.Parameters of helicopter FCS and dimensions of MHT are simultaneously optimized using a stochastic optimization method, namely, simultaneous perturbation stochastic approximation (i.e., SPSA).In order to observe improvement in behaviors of classical controls closed loop analyses are done.

View Article: PubMed Central - PubMed

Affiliation: College of Aviation, Erciyes University, 38039 Kayseri, Turkey.

ABSTRACT
Helicopter moving horizontal tail (i.e., MHT) strategy is applied in order to save helicopter flight control system (i.e., FCS) energy. For this intention complex, physics-based, control-oriented nonlinear helicopter models are used. Equations of MHT are integrated into these models and they are together linearized around straight level flight condition. A specific variance constrained control strategy, namely, output variance constrained Control (i.e., OVC) is utilized for helicopter FCS. Control energy savings due to this MHT idea with respect to a conventional helicopter are calculated. Parameters of helicopter FCS and dimensions of MHT are simultaneously optimized using a stochastic optimization method, namely, simultaneous perturbation stochastic approximation (i.e., SPSA). In order to observe improvement in behaviors of classical controls closed loop analyses are done.

No MeSH data available.