0
Journal of Dynamic Systems, Measurement, and Control | Volume 138 | Issue 8 | research-article
Research Papers

Finite-Time Regulation of Two-Spool Turbofan Engines With One Shaft Speed Control

[+] Author and Article Information
Jiqiang Wang

Jiangsu Province Key Laboratory
of Aerospace Power Systems,
Nanjing University of Aeronautics
and Astronautics,
Nanjing 210016, China;AVIC Shenyang Engine Design
and Research Institute,
Shenyang 110015, China
e-mail: jiqiang.wang@nuaa.edu.cn

Georgi Dimirovski

Department of Computing and
Control Engineering,
Dogus University of Istanbul,
Istanbul 34722, Turkey
e-mail: gdimirovski@dogus.edu.tr

Hong Yue

Industrial Control Centre,
University of Strathclyde,
Glasgow G1 1XW, UK
e-mail: hong.yue@strath.ac.uk

Contributed by the Dynamic Systems Division of ASME for publication in the JOURNAL OF DYNAMIC SYSTEMS, MEASUREMENT, AND CONTROL. Manuscript received July 1, 2015; final manuscript received March 24, 2016; published online May 25, 2016. Assoc. Editor: Junmin Wang.

J. Dyn. Sys., Meas., Control 138(8), 081005 (May 25, 2016) (7 pages) Paper No: DS-15-1297; doi: 10.1115/1.4033310 History: Received July 01, 2015; Revised March 24, 2016
Article
References
Figures

Nonlinear control of aircraft engines has attracted much attention in consideration of the inherent nonlinearity of the engine dynamics. Most of the nonlinear design techniques, however, require the information from the rotational speeds of both high-pressure compressor and fan. This is not desirable from engine health management perspective, and this paper proposes a single sensor measurement and single actuator control approach. The proposed method can provide fast regulation of engine speed in a finite-time in comparison with conventional infinite time stability. Important results are obtained on both controller design and disturbance tolerance. Numerical examples are provided for validation of the proposed finite-time controller, demonstrating fast regulation property and remarkable disturbance tolerance capability.
FIGURES IN THIS ARTICLE
<>
Copyright © 2016 by ASME
Your Session has timed out. Please sign back in to continue.

References

Figures

Grahic Jump Location
Fig. 1

Schematic representation of three basic functions of control system as reflected in a compressor map

+Schematic representation of three basic functions of control system as reflected in a compressor map
View Large  |  Save Figure  |  Download Slide (.ppt)
Schematic representation of three basic functions of control system as reflected in a compressor map
Grahic Jump Location
Fig. 2

Performance of the finite-time control with two-sensor measurements and PI control

+Performance of the finite-time control with two-sensor measurements and PI control
View Large  |  Save Figure  |  Download Slide (.ppt)
Performance of the finite-time control with two-sensor measurements and PI control
Grahic Jump Location
Fig. 3

Control signals for both finite-time control with two-sensor measurements and PI control

+Control signals for both finite-time control with two-sensor measurements and PI control
View Large  |  Save Figure  |  Download Slide (.ppt)
Control signals for both finite-time control with two-sensor measurements and PI control
Grahic Jump Location
Fig. 4

Performance of the finite-time control: one-sensor versus two-sensor measurement

+Performance of the finite-time control: one-sensor versus two-sensor measurement
View Large  |  Save Figure  |  Download Slide (.ppt)
Performance of the finite-time control: one-sensor versus two-sensor measurement
Grahic Jump Location
Fig. 5

Control signals for finite-time control: one-sensor versus two-sensor measurement

+Control signals for finite-time control: one-sensor versus two-sensor measurement
View Large  |  Save Figure  |  Download Slide (.ppt)
Control signals for finite-time control: one-sensor versus two-sensor measurement
Grahic Jump Location
Fig. 6

Performance of the single sensor measurement and single actuator finite-time controller (27) under persistent disturbance of magnitude A = 2

+Performance of the single sensor measurement and single actuator finite-time controller (27) under persistent disturbance of magnitude A = 2
View Large  |  Save Figure  |  Download Slide (.ppt)
Performance of the single sensor measurement and single actuator finite-time controller (27) under persistent disturbance of magnitude A = 2
Grahic Jump Location
Fig. 7

Control signals for both finite-time controller (27) and PI control under disturbances

+Control signals for both finite-time controller (27) and PI control under disturbances
View Large  |  Save Figure  |  Download Slide (.ppt)
Control signals for both finite-time controller (27) and PI control under disturbances
Grahic Jump Location
Fig. 8

Performance of the single sensor measurement and single actuator finite-time controller (27) under persistent disturbance of different magnitudes: left to the legend is the magnified view for low-pressure turbine speed ΔnL

+Performance of the single sensor measurement and single actuator finite-time controller (27) under persistent disturbance of different magnitudes: left to the legend is the magnified view for low-pressure turbine speed ΔnL
View Large  |  Save Figure  |  Download Slide (.ppt)
Performance of the single sensor measurement and single actuator finite-time controller (27) under persistent disturbance of different magnitudes: left to the legend is the magnified view for low-pressure turbine speed ΔnL

Tables

Errata

Discussions

Some tools below are only available to our subscribers or users with an online account.

Related Content

Customize your page view by dragging and repositioning the boxes below.

Related Journal Articles
Related eBook Content
Characteristics Measurement and FPGA Controller Design for an Air Motor and Electric Motor Hybrid Power System
International Conference on Instrumentation, Measurement, Circuits and Systems (ICIMCS 2011)
Stable Analysis on Speed Adaptive Observer in Low Speed Operation
International Conference on Instrumentation, Measurement, Circuits and Systems (ICIMCS 2011)
Adaptive Neural Controller for a Permanent Magnet DC Motor
Intelligent Engineering Systems through Artificial Neural Networks
Application of Neural Sliding Mode Control for PMLSM Servo System
International Conference on Mechanical and Electrical Technology, 3rd, (ICMET-China 2011), Volumes 1–3
Application of a Variable-Universe and Self-Adaptive Fuzzy PID Controller in DC Motor Speed Control System
International Conference on Mechanical Engineering and Technology (ICMET-London 2011)
Topic Collections

Sorry! You do not have access to this content. For assistance or to subscribe, please contact us:

  • TELEPHONE: 1-800-843-2763 (Toll-free in the USA)
  • EMAIL: asmedigitalcollection@asme.org
Sign In