A380 Roll Kinematics Design

Delannoy, Stéphane

doi:10.3182/20070625-5-fr-2916.00019

Cited by 1 publication

(1 citation statement)

References 0 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The consequence is that the FCS functional architecture may consist of a large number of control effectors. Distributed roll mechanisms such as in-board/out-board ailerons and roll spoilers [1] are common examples, as are high-lift devices such as flaps and slats. More extensive and complex system architectures are seen in case of extreme maneuvering capabilities and high angle-of-attack flight.…”

Section: Introductionmentioning

confidence: 99%

Multi-objective Design and Performance Analysis of Incremental Control Allocation-based Flight Control Laws

Pollack

Kampen

2023

AIAA SCITECH 2023 Forum

View full text Add to dashboard Cite

The functional architecture of a flight control system (FCS) is driven by multiple objectives related to the aircraft's operational mission and in-service performance targets. Control allocation (CA) is a common method to ensure adequate use of the available effector architecture once the number of control effectors linked to the FCS increases and the control problem becomes overdetermined. A primary CA design objective is to ensure that high-level motion control demands are met. However, the additional degrees of freedom offered by the control effector suite can also be exploited to perform secondary control tasks. In this light, this article focuses on the Incremental Control Allocation (INCA) framework in the context of in-flight optimization of arbitrary secondary flight control design objectives. An extension to the existing INCA concept is formulated that isolates this secondary control task from generating primary control demands. Moreover, an alternative, but closely related design method based on optimal control principles is proposed that extents the role of the control allocator to active control of the system dynamics. Design examples are demonstrated for least-squares minimization of total drag and control activity. These are analyzed in linear and nonlinear simulation scenarios based on an open-source General Dynamics F-16 simulation model.

show abstract

Section: Introductionmentioning

confidence: 99%