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Research Papers

Output Feedback Control Surface Positioning With a High-Order Sliding Mode Controller/Estimator: An Experimental Study on a Hydraulic Flight Actuation System

[+] Author and Article Information
Ali Şener Kaya

Guidance and Control Research Department,
Roketsan Missile Industries,
Ankara 06780, Turkey
e-mail: skaya@roketsan.com.tr

Mehmet Zeki Bilgin

Electrical Engineering Departments,
Faculty of Engineering,
Kocaeli University, Izmit 41380, Turkey
e-mail: bilgin@kocaeli.edu.tr

1Corresponding author.

Contributed by the Dynamic Systems Division of ASME for publication in the JOURNAL OF DYNAMIC SYSTEMS, MEASUREMENT,AND CONTROL. Manuscript received December 4, 2017; final manuscript received May 20, 2018; published online September 21, 2018. Assoc. Editor: Heikki Handroos.

J. Dyn. Sys., Meas., Control 141(1), 011009 (Sep 21, 2018) (10 pages) Paper No: DS-17-1602; doi: 10.1115/1.4040436 History: Received December 04, 2017; Revised May 20, 2018

In this paper, an output feedback sliding mode position controller/estimator scheme is proposed to control an single input single output (SISO) system subject to bounded nonlinearities and parametric uncertainties. Various works have been published addressing the theoretical effectiveness of the third-order sliding mode control (3-SMC) in terms of chattering alleviation and controller robustness. However, the application of 3-SMC with a feedback estimator to a flight actuators has not been treated explicitly. This is due to the fact that the accurate full state estimation is required since SMCs performance can be severely degraded by measurement or estimation noise. Aerodynamic control surface actuators in air vehicles mostly employ linear position controllers to achieve guidance and stability. The main focus of the paper is to experimentally demonstrate the stability and positioning performance of a third-order SMC applied to a class of system with high relative degree and bounded parametric uncertainties. The performance of the closed-loop system is also compared with a lower level SMC and classical controller to show the effectiveness of the algorithm. Realization of the proposed algorithm from an application perspective is the main target of this paper and it demonstrates that a shorter settling time and higher control action attenuation can be achieved with the proposed strategy.

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Figures

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Fig. 1

Flight control actuator linked to a control surface

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Fig. 2

Phase portrait of the sliding surface variables

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Fig. 4

Velocity estimation of from the position signal: (a) amplitude variation, (b) phase variation, (c) estimation sampled at 30 Hz, (d) estimation sampled at 5 Hz, (e) estimation error, and (f) estimation sampled at 60 Hz

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Fig. 5

Acceleration estimation of from the position signal: (a) amplitude variation, (b) estimation error, (c) estimation sampled at 30 Hz, and (d) estimation sampled at 60 Hz

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Fig. 6

(a) Comparison of the position response and control cost from simulation and experiment. (b) Zoomed position transient area. (b) Zoomed position steady-state area. (c) control cost variation (maximum control cost output is 20 mA, which corresponds to %100 control effort).

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Fig. 7

(a) Step position response obtained from experiment. Transient and steady-state regions are represented as I and II, respectively: (a) zoomed transient region, (b) zoomed steady-state region, (c) transient control cost variation, and (d) steady-state control cost variation.

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Fig. 3

Schematic view of the real-time controller (left) and hydraulic flight control actuator (right). Left-side figure, Courtesy of Liebherr Aerospace. Right-side figure, credited by: Hannes Grobe.

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