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Technical Brief

Tracking Control of Limit Cycle Oscillations in an Aero-Elastic System

[+] Author and Article Information
B. J. Bialy

Department of Mechanical and Aerospace Engineering,
University of Florida,
Gainesville, FL 32611
e-mail: bialybj@ufl.edu

Crystal L. Pasiliao

Air Force Research Laboratory,
Munitions Directorate,
Eglin AFB, FL 32542
e-mail: crystal.pasiliao@eglin.af.mil

H. T. Dinh

Department of Mechanical and Aerospace Engineering,
University of Florida,
Gainesville, FL 32611
e-mail: huyentdinh@ufl.edu

W. E. Dixon

Department of Mechanical and Aerospace Engineering,
University of Florida,
Gainesville, FL 32611
e-mail: wdixon@ufl.edu

See [15] for details.

1Corresponding author.

Contributed by the Dynamic Systems Division of ASME for publication in the JOURNAL OF DYNAMIC SYSTEMS, MEASUREMENT, AND CONTROL. Manuscript received July 18, 2013; final manuscript received June 25, 2014; published online August 8, 2014. Assoc. Editor: Yang Shi.

J. Dyn. Sys., Meas., Control 136(6), 064505 (Aug 08, 2014) (5 pages) Paper No: DS-13-1277; doi: 10.1115/1.4027946 History: Received July 18, 2013; Revised June 25, 2014

Limit cycle oscillations (LCOs) affect current fighter aircraft and are expected to be present on next generation fighter aircraft. Current efforts in control systems designed to suppress LCO behavior have either used a linear model, restricting the flight regime, require exact knowledge of the system dynamics, or require uncertainties in the system dynamics to be linear-in-the-parameters and only present in the torsional stiffness. Furthermore, the aerodynamic model used in prior research efforts neglects nonlinear effects. This paper presents the development of a controller consisting of a continuous robust integral of the sign of the error (RISE) feedback term with a neural network (NN) feedforward term to achieve asymptotic tracking of uncertainties that do not satisfy the linear-in-the-parameters assumption. Simulation results are presented to validate the performance of the developed controller.

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References

Figures

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Fig. 1

Aero-elastic system free response without disturbances

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Fig. 2

Aero-elastic system states in the presence of an additive disturbance

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Fig. 3

Control surface deflection, δ(t), for the developed controller and the controller from Ref. [12]

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Fig. 4

Monte Carlo AOA trajectories

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Fig. 5

Monte Carlo vertical position trajectories

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Fig. 6

Monte Carlo control effort

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