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Research Papers

Gain-Scheduled Two-Loop Autopilot for an Aircraft

[+] Author and Article Information
Laleh Ravanbod

Université Paul Sabatier,
Institut de Mathématiques,
Toulouse 31062, France
e-mail: LalehRavanbod@yahoo.fr

Dominikus Noll

Professor
Université Paul Sabatier,
Institut de Mathématiques,
Toulouse 31062, France
e-mail: d.noll@math.univ-toulouse.fr

Contributed by the Dynamic Systems Division of ASME for publication in the JOURNAL OF DYNAMIC SYSTEMS, MEASUREMENT, AND CONTROL. Manuscript received August 14, 2012; final manuscript received February 6, 2014; published online April 28, 2014. Assoc. Editor: Yang Shi.

J. Dyn. Sys., Meas., Control 136(4), 041021 (Apr 28, 2014) (13 pages) Paper No: DS-12-1262; doi: 10.1115/1.4026832 History: Received August 14, 2012; Revised February 06, 2014

We present a new method to compute output gain-scheduled controllers for nonlinear systems. We use structured H-control to precompute an optimal controller parametrization as a reference. We then propose three practical methods to implement a control law which has only an acceptable loss of performance with regard to the optimal reference law. Our method is demonstrated in longitudinal flight control, where the dynamics of the aircraft depend on the operational conditions velocity and altitude. We design a structured controller consisting of a PI-block to control vertical acceleration, and another I-block to control the pitch rate.

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References

Figures

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Fig. 1

rct_airframe1 scheme of simulink

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Fig. 2

Schemes used for (a) linearizing the nonlinear aircraft in closed-loop and (b) H synthesis

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Fig. 3

Left: flight envelope in geometry (M,q¯). Right: optimal H performance over flight envelope geometry e = (h, V).

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Fig. 4

Graphs of the optimal gains ki*(e),kp*(e), and kg*(e) and the optimal closed-loop performance (lower right) displayed over E

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Fig. 5

Two triangulations together with the performance graphs

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Fig. 6

Example of preprocessing of the regions N(e): (a) without smoothing and (b) with smoothing

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Fig. 7

Seven regions N(ei) which cover E, performance error margin is respected in Eq. (2)

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Fig. 8

Performance optimal (left) and its estimation by greedy (right)

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Fig. 9

First approximation of the controller parameters and the performance obtained

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Fig. 10

Second approximation of the controller parameters and its performance

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Fig. 11

Detectability rate, respectively, e→‖(sI-Acl(e))-1Bcl(e)‖∞, visualized over the flight envelope E. Ideal K* upper left, Kint upper right, Ktri (35 controllers) lower left, and Kgreedy lower right.

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Fig. 12

Vertical acceleration hold for high altitude

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Fig. 13

Vertical acceleration hold for low altitude

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Fig. 14

Control scheme for flight control

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Fig. 15

Optimal performance for flight control case

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