Detail publikace

Evolution Driven Controller Design for Aeroservoelastic Aircraft

Originální název

Evolution Driven Controller Design for Aeroservoelastic Aircraft

Anglický název

Evolution Driven Controller Design for Aeroservoelastic Aircraft

Jazyk

en

Originální abstrakt

An evolution driven controller design approach has been applied to an aeroservoelastic model of a large passenger aircraft. The aeroservoelastic model comprises structural, aerodynamic and flight dynamics related elements and the chosen controller architecture is based on Nonlinear Dynamic Inversion. The evolutionary concept has played a significant role in the optimization of the proposed NDI controller structure by providing tuned controller parameters which meet the designed fitness function criteria imposed through the optimization problem formulation. The proposed fitness function combines significant controller stability evaluation criteria into a single abstraction. The use of a robust optimization framework based on the genetic algorithms has allowed the suggested form of multi-criteria optimization definition. The suitability of the evolutionary optimization has been successfully tested on a set of examples, which accounted for rigid body aircraft dynamics as well as for the case with elastic structural modes. Time-domain simulation results have shown the compliance of the tuned controller performance to its anticipated behavior.

Anglický abstrakt

An evolution driven controller design approach has been applied to an aeroservoelastic model of a large passenger aircraft. The aeroservoelastic model comprises structural, aerodynamic and flight dynamics related elements and the chosen controller architecture is based on Nonlinear Dynamic Inversion. The evolutionary concept has played a significant role in the optimization of the proposed NDI controller structure by providing tuned controller parameters which meet the designed fitness function criteria imposed through the optimization problem formulation. The proposed fitness function combines significant controller stability evaluation criteria into a single abstraction. The use of a robust optimization framework based on the genetic algorithms has allowed the suggested form of multi-criteria optimization definition. The suitability of the evolutionary optimization has been successfully tested on a set of examples, which accounted for rigid body aircraft dynamics as well as for the case with elastic structural modes. Time-domain simulation results have shown the compliance of the tuned controller performance to its anticipated behavior.

BibTex


@inproceedings{BUT103559,
  author="Peter {Chudý} and Miguel {Leitao} and Felix {Stroscher} and Jan {Vlk}",
  title="Evolution Driven Controller Design for Aeroservoelastic Aircraft",
  annote="An evolution driven controller design approach has been applied to an
aeroservoelastic model of a large passenger aircraft. The aeroservoelastic model
comprises structural, aerodynamic and flight dynamics related elements and the
chosen controller architecture is based on Nonlinear Dynamic Inversion. The
evolutionary concept has played a significant role in the optimization of the
proposed NDI controller structure by providing tuned controller parameters which
meet the designed fitness function criteria imposed through the optimization
problem formulation. The proposed fitness function combines significant
controller stability evaluation criteria into a single abstraction. The use of
a robust optimization framework based on the genetic algorithms has allowed the
suggested form of multi-criteria optimization definition. The suitability of the
evolutionary optimization has been successfully tested on a set of examples,
which accounted for rigid body aircraft dynamics as well as for the case with
elastic structural modes. Time-domain simulation results have shown the
compliance of the tuned controller performance to its anticipated behavior.",
  address="American Institute of Aeronautics and Astronautics",
  booktitle="Conference Proceeding Series (GNC/AFM/MST)",
  chapter="103559",
  doi="10.2514/6.2013-5153",
  edition="AIAA Modeling and Simulation Technologies (MST) Conference",
  howpublished="online",
  institution="American Institute of Aeronautics and Astronautics",
  year="2013",
  month="august",
  pages="1--17",
  publisher="American Institute of Aeronautics and Astronautics",
  type="conference paper"
}