In-flight Simulation of an Aircraft Using Linear Quadratic Gaussian Controller

Document Type : Case Study


Engineering Department, Islamic Azad University, Damghan Branch, Damghan, Iran


The in-flight simulator is one of the various kinds of aircraft simulators at which a real aircraft provides a platform for simulating the dynamic responses of another aircraft. In this paper, the capability of the in-flight simulation of an aircraft by a host aircraft simulator using the linear quadratic gaussian (LQG) controller is presented. Initially, the maximum likelihood algorithm and the flight test data are used to estimate the aerodynamic derivatives of the guest aircraft and consequently drive its high-order aerodynamic model. Then, the linear and nonlinear models of both aircraft in the longitudinal and lateral modes are constructed and the proper LQG controllers are designed for the in-flight simulation of the guest aircraft responses caused by the host aircraft simulator. Next, by applying different commands to the control surfaces of the guest aircraft, its linear and nonlinear dynamic responses are simulated in the longitudinal and lateral modes. Finally, the simulated flight profiles of the guest aircraft are tracked by the host aircraft simulator in the linear and nonlinear schemes. To validate the capability of the LQG controllers for tracking the guest aircraft response, the flight test profile of the guest aircraft is also simulated by the host aircraft simulator.


Main Subjects

[1] M. Lone, A. Cooke, Review of pilot models used in aircraft flight dynamics. Aerospace Science and Technology, 34 (2014) 55-74.
[2] P.A. Reynolds, Total In-Flight Simulator (TIFS)-A New Aircraft Design Tool, Journal of Aircraft, 9(6) (1972) 392-398.
[3] N.C. Weingarten, An In-Flight Investigation of Various Longitudinal Flight Control Systems in the Space Shuttle Orbiter during Approach and Landing, Technical Report 7263-1, Arvin/Calspan Advanced Technology Center, Buffalo, NY; Dec 1985.
[4] M. Malekzadeh, H. Sadeghian, Attitude control of spacecraft simulator without angular velocity measurement, Control Engineering Practice, 84 (2019) 72-81.
[5] N.C. Weingarten, In-Flight Simulation of the Space Shuttle Orbiter during Landing Approach and Touchdown in the Total In-Flight Simulator (TIFS), Technical Report 6339-F-1, Arvin/Calspan Advanced Technology Center, Buffalo, NY; Sep. 1978.
[6] M.F. Shafer, Inflight Simulation Studies at NASA Dryden Flight Research Facility, Dryden Flight Center. NASA Technical Memorandum 4396, Edwards, California, 1992.
[7] B.G. Powers, S.K. Sarrafian, Simulation Studies of Alternate Longitudinal Control Systems for the Space Shuttle Orbiter in the Landing Regime, In AIAA Atmospheric Flight Mechanics Conference Proceedings. Virginia: Williamsburg, Aug 1986, AIAA-86-2127, pp 182–192.
[8] K. Johansson, P. Dyreklev, O. Granbom, M.C. Calver, S. Fourtine, Feuillatre o. In-flight and ground testing of single event upset sensitivity in static RAMs, IEEE Transactions on Nuclear Science, 45(3) (1998) 1628-1632.
[9] D.T. Berry, B.G. Powers, K.J. Szalai, R.J. Wilson, In-Flight Evaluation of Control System Pure Time Delays, Journal of Aircraft, 19(4) (1982) 318–323.
[10] M. Sato, Gain-Scheduled Flight Controller Using Bounded Inexact Scheduling Parameters, IEEE Transactions on Control Systems Technology, 27(3) (2018) 1074-1082.
[11] M. Sato, A. Satoh, Flight Control Experiment of Multipurpose-Aviation-Laboratory-alpha In-Flight Simulator. Journal of Guidance, Control, and Dynamics, 34(4) (2011) 1081-1096.
[12] S. Corda, R.J. Franz, J.N. Blanton, M.J. Vachon, J.B. Deboer, In-Flight Vibration Environment of the NASA F-15B Flight Test Fixture. NASA/TM-2002-210719, NASA Dryden Flight Research Center, Edwards, California, February 2002.
[13] N.C. Weingarten, History of In-Flight Simulation & Flying Qualities Research at Calspan, Journal of Aircraft, 42(2) (2005) 1-16.
[14] C. Kim, A. Study on the Design and Validation of Switching Control Law, Journal of Institute of Control, Robotics and Systems, 17(1) (2011) 54-60.
[15] S. Fernandes, Guidance and Trajectory Following of an Autonomous Vision-Guided Micro Quadrotor, Lisbon, Portugal: Universidade Tecnica de Lisboa, 2011.
[16] A.A. Pashilkar, Trends in Simulation Technologies for Aircraft Design, Journal of Aerospace Science and Technology, 22(1) (2014) 1-10.
[17] S.J. Mohammadi, M. Mortazavi, Design of Tracking Controller for In-flight Simulation of Fighter Aircraft by UAV Platform, Mechanical Engineering Tabriz University, 47(3) (2017) 234-235.
[18] D.C. Watson, W.S. Hindson, In-flight simulation investigation of rotorcraft pitch-roll cross coupling, NationalAeronautics and Space Administration, NASA, 2018.
[19] M.S. Chehadeh, Design of rules for in-flight non-parametric tuning of PID controllers for unmanned aerial vehicles, Journal of the Franklin Institute 356(1) (2019) 474-491
[20] B.L. Stevens, F.L. Lewis, Aircraft Control and Simulation, New York: John Wiley & Sons, 1992.
[21] J. Roskam, Airplane Flight Dynamics and Automatic Flight Control, Kansas: Lawrence University, 1979.
[22] R.C. Nelson, Flight Stability and Automatic Control, New York: McGraw-Hill, 1989.
[23] U. Ozdemir, M.S. Kavsaoglu, Linear and Nonlinear Simulation of Aircraft Dynamics Using Body Axis System, International Journal of aircraft engineering and aerospace technology, 80(6) (2008) 638-648.
[24] R.E. Maine, K.W. Iliff, Identification of Dynamic Systems-Applications to Aircraft. Part 1. The Output Error Approach, AGARD Flight Test Techniques-AG300, vol. 3, 1986.
[25] R.D. Grove, R.L. Bowles, S.C. Mayhew, A Procedure for Estimating Stability and Control Parameters from Flight Test Data by Using Maximum Likelihood Method Employing a Real Time Digital System, NASA TN D-6735, Washington, US; May 1972.
[26] M. Safi, M. Mortazavi, S. M. Dibaji, Global Stabilization of Attitude Dynamics: SDRE-based Control Designs, AUT Journal of Modeling and Simulation, 50(2) (2018) 203-210.
[27] L.W. Taylor, K.W. Iliff, System Identification Using a Modified Newton Raphson Method- A FORTRAN Program, NASA TN D-6734,Washington, US, May 1972.
[28] S. Skogestad, I. Postlethwaite, Multivariable Feedback Control-Analysis and Design, New York: John Wiley & Sons, 2005.
[29] J.L. Speyer, W.H. Chung, Stochastic Processes, Estimation, and Control (Advances in Design and Control), Los Angeles: Published by Society for Industrial Applied Mathematics, university of California, 2011.
[30] S. Hur, W.E. Leithead, Model predictive and linear quadratic Gaussian control of a wind turbine. Optimal Control, application, and methods, 38(1) (2017) 88-111.