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Journal of Dynamic Systems, Measurement, and Control | Volume 138 | Issue 2 | Technical Brief
Technical Brief

Design of Automatic Landing Systems Using the H-inf Control and the Dynamic Inversion

[+] Author and Article Information
Romulus Lungu

Electrical, Energetic, and Aerospatiale
Engineering Department,
University of Craiova,
107 Decebal Street,
Craiova 200440, Romania
e-mail: romulus_lungu@yahoo.com

Mihai Lungu

Electrical, Energetic, and Aerospatiale
Engineering Department,
University of Craiova,
107 Decebal Street,
Craiova 200440, Romania
e-mail: Lma1312@yahoo.com

1Corresponding author.

Contributed by the Dynamic Systems Division of ASME for publication in the JOURNAL OF DYNAMIC SYSTEMS, MEASUREMENT, AND CONTROL. Manuscript received January 3, 2015; final manuscript received November 11, 2015; published online December 11, 2015. Assoc. Editor: Manish Kumar.

J. Dyn. Sys., Meas., Control 138(2), 024501 (Dec 11, 2015) (5 pages) Paper No: DS-15-1002; doi: 10.1115/1.4032028 History: Received January 03, 2015; Revised November 11, 2015
Article
References
Figures

This paper focuses on the automatic control of aircraft in the longitudinal plane, during landing, by using the linearized dynamics of aircraft, taking into consideration the wind shears and the errors of the sensors. A new robust automatic landing system (ALS) is obtained by means of the H-inf control, the dynamic inversion, an optimal observer, and two reference models providing the aircraft desired velocity and altitude. The theoretical results are validated by numerical simulations for a Boeing 747 landing; the simulation results are very good (Federal Aviation Administration (FAA) accuracy requirements for Category III are met) and show the robustness of the system even in the presence of wind shears and sensor errors. Moreover, the designed control law has the ability to reject the sensor measurement noises and wind shears with low intensity.
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References

1
McLean, D. , 1990, Automatic Flight Control Systems, Prentice Hall, Englewood Cliffs, NJ.
2
Lungu, R. , Lungu, M. , and Grigorie, T. L. , 2012, “ ALSs With Conventional and Fuzzy Controllers Considering Wind Shears and Gyro Errors,” J. Aerosp. Eng., 26(4), pp. 794–813. [CrossRef]
3
Lungu, R. , Lungu, M. , and Grigorie, T. L. , 2013, “ Automatic Control of Aircraft in Longitudinal Plane During Landing,” IEEE Trans. Aerosp. Electron. Syst., 49(2), pp. 1338–1350. [CrossRef]
4
Juang, J. G. , and Cheng, K. C. , 2006, “ Application of Neural Network to Disturbances Encountered Landing Control,” IEEE Trans. Intell. Transp. Syst., 7(4), pp. 582–588. [CrossRef]
5
Che, J. , and Chen, D. , 2001, “ Automatic Landing Control Using H∞ Control and Stable Inversion,” 40th Conference on Decision and Control, Orlando, FL, pp. 241–246.
6
Li, Y. , Sundararajan, N. , Saratchandran, P. , and Wang, Z. , 2004, “ Robust Neuro-H∞ Controller Design for Aircraft Auto-Landing,” IEEE Trans. Aerosp. Electron. Syst., 40(1), pp. 158–167. [CrossRef]
7
Mori, R. , and Suzuki, S. , 2009, “ Neural Network Modeling of Lateral Pilot Landing Control,” J. Aircr., 46(5), pp. 1721–1726. [CrossRef]
8
Vo, H. , and Sridhar, S. , 2008, “ Robust Control of F-16 Lateral Dynamics,” Int. J. Aerosp. Mech. Eng., 2(2), pp. 80–85.
9
Rao, D. M. , and Go, T. H. , 2014, “ Automatic Landing System Design Using Sliding Mode Control,” Aerosp. Sci. Technol., 32, pp. 180–187. [CrossRef]
10
Zdenko, K. , and Stjepan, B. , 2006, Fuzzy Controller Design—Theory and Applications, Taylor and Francis, Boca Raton.
11
Kumar, V. , Rana, K. P. , and Gupta, V. , 2008, “ Real-Time Performance Evaluation of a Fuzzy PI + Fuzzy PD Controller for Liquid-Level Process,” Int. J. Intell. Control Syst., 13(2), pp. 89–96.
12
Shue, S. , and Agarwal, R. K. , 1999, “ Design of Automatic Landing Systems Using Mixed H2/H∞ Control,” J. Guid. Control Dyn., 22(1), pp. 103–114. [CrossRef]
13
Ochi, Y. , and Kanai, K. , 1999, “ Automatic Approach and Landing for Propulsion Controlled Aircraft by H∞ Control,” 1999 IEEE International Conference on Control Applications, Kohala Coast, HI, pp. 997–1002.
14
Afshari, H. , Roshanian, J. , and Novinzadeh, A. , 2011, “ Robust Nonlinear Optimal Solution to the Lunar Landing Guidance by Using Neighboring Optimal Control,” J. Aerosp. Eng., 24(1), pp. 20–30. [CrossRef]
15
Lungu, M. , 2008, Sisteme de Conducere a Zborului (Flight Control Systems), Sitech, Craiova, Romania.
16
Parkinson, B. , O'Connor, M. , and Fitzgibbon, K. , 1996, “ Aircraft Automatic Approach and Landing Using GPS,” Global Positioning System: Theory and Applications, Vol. II, AIAA, Cambridge, UK, pp. 397–425.
17
Tudosie, A. , 2008, “ Jet Engine's Speed Controller With Constant Pressure Chamber,” International Conference on Automation and Information ICAI'08, Bucharest, Romania, pp. 229–234.
18
Braff, R. , Powell, J. D. , and Dorfler, J. , 1996, “ Applications of GPS to Air Traffic Control,” Global Positioning System: Theory and Applications, Vol. II, AIAA, Cambridge, UK, pp. 327–374.

Figures

Grahic Jump Location
Fig. 1

New ALS using dynamic inversion and H-inf method

+New ALS using dynamic inversion and H-inf method
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New ALS using dynamic inversion and H-inf method
Grahic Jump Location
Fig. 2

Block diagrams of the third-order and second-order reference models, respectively: (a) simplified block diagram and (b) detailed block diagram

+Block diagrams of the third-order and second-order reference models, respectively: (a) simplified block diagram and (b) detailed block diagram
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Block diagrams of the third-order and second-order reference models, respectively: (a) simplified block diagram and (b) detailed block diagram
Grahic Jump Location
Fig. 5

Aircraft altitude errors for different values of matrix D22

+Aircraft altitude errors for different values of matrix D22
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Aircraft altitude errors for different values of matrix D22
Grahic Jump Location
Fig. 3

Time characteristics for the glide slope phase, with or without sensor errors

+Time characteristics for the glide slope phase, with or without sensor errors
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Time characteristics for the glide slope phase, with or without sensor errors
Grahic Jump Location
Fig. 4

Time characteristics for the flare phase, with or without sensor errors

+Time characteristics for the flare phase, with or without sensor errors
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Time characteristics for the flare phase, with or without sensor errors

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