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In the paper implementation of a ground control station for UAV flight simulator is shown. The ground control station software is in cooperation with flight simulator, displaying various aircraft flight parameters. The software is programmed in C++ language and utilizes the windows forms for implementing graphical content. One of the main aims of the design of the application was to simplify the interface, simultaneously maintaining the functionality and the eligibility. A mission can be planned and monitored using the implemented map control supported by waypoint list.

6. References 1. Boril J., Jalovecky R.: Experimental Identification of Pilot Response Using Measured Data from a Flight Simulator. In: Iliadis L., Maglogiannis I., Papadopoulos H. (eds) Artificial Intelligence Applications and Innovations. AIAI 2012. IFIP Advances in Information and Communication Technology, Springer, vol. 381, Berlin, Heidelberg, 2012, DOI: 10.1007/978-3-642-33409-2_14. 2. Cameron N., Thomson D.G., Murray-Smith D.J.: Pilot modelling and inverse simulation for initial handling qualities assessment. Aeronautical Journal, 2003. 3. Carver J

Assessment of Flight Simulator Fidelity Using Pilot Models, Journal of Guidance, Control and Dynamics 32 (2009), 760–770. HESS R. A. MARCHESI F. Analytical Assessment of Flight Simulator Fidelity Using Pilot Models Journal of Guidance, Control and Dynamics 32 2009 760 770 [14] HESS, R. A.—SIWAKOSIT, W. : Assessment of Flight Simulator Fidelity in Multiaxis Tasks Including Visual Cue Quality, Journal of Aircraft 38 (2001), 607–614. HESS R. A. SIWAKOSIT W. Assessment of Flight Simulator Fidelity in Multiaxis Tasks Including Visual Cue Quality Journal of Aircraft 38 2001


This paper considered a problem of: the reliability of performance of a nosedive of a jet powered aircraft in the context of the ability of pilots trained on a simulator to reliably accomplish a combat mission. For research purposes, the manoeuvre of attack of a target with the nosedive, which is most commonly used by the pilots performing flights on different types of modern aircrafts, and the basic manoeuvre during aircrew training, both basic and advanced were assumed. The research was conducted on a flight simulator.

7. References 1. UK Civil Aviation Authority: CAP 698 CAA JAR-FCL Examinations Aeroplane Performance Manual, Third Edition July 2006. 2. U.S. Department of Transportation FEDERAL AVIATION ADMINISTRATION: Pilot’s Handbook of Aeronautical Knowledge 2016. 3. CAE Oxford Aviation Academy: Mass and Balance + Performance, ATPL Ground Training Series (030 032), Oxford 2018. 4. Daněk V.: Performance, ATPL theory (030 032), Brno, 2006. 5. Kaľavský P., Gazda J., Rozenberg R., Mikula B.: Flight simulators for general aviation. In: Safety and Transport. Brno: CERM, 2017. 6

Sliding mode methods for fault detection and fault tolerant control with application to aerospace systems

Sliding mode methods have been historically studied because of their strong robustness properties with regard to a certain class of uncertainty, achieved by employing nonlinear control/injection signals to force the system trajectories to attain in finite time a motion along a surface in the state-space. This paper will consider how these ideas can be exploited for fault detection (specifically fault signal estimation) and subsequently fault tolerant control. It will also describe applications of these ideas to aerospace systems, including piloted flight simulator results associated with the GARTEUR AG16 Action Group on Fault Tolerant Control. The results demonstrate a successful real-time implementation of the proposed fault tolerant control scheme on a motion flight simulator configured to represent the post-failure EL-AL aircraft.


The article presents selected results of the analytical work carried out in the Air Force Institute of Technology and the Polish Air Force Academy by means of a computer simulation of noncommutativity phenomena submitting aircraft turnover on high-manoeuvrability flights. The results of these simulations allowed to define the guidelines for the method of “production” of noncommutativity phenomenon in specialized rotating positions for strapdown inertial navigation systems (to evaluate the errors of determining spatial orientation).

Also, it analysed the possibility of “production” noncommutativity rotational movement in mobile flight simulator used for testing pilots and candidates for pilots (to test the sensitivity of the pilot’s vestibular system in terms of feeling the impact of this phenomenon). The results of the assessment of “greatness” noncommutativity angular velocity vector, occurring in some parts of the high-manoeuvrability flight of aircraft on the example of a fighter-bomber airplane Su-22 were discussed as well.

5. References 1. CKAS Flight Simulator Operating Manual. 2. Ignac-Nowicka J., Gembalska-Kwiecień A.: Niezawodność człowieka i niezawodność techniczna w procesie pracy układu człowiek - maszyna. Inżynieria Systemów technicznych, 2014. 3. Lewitowicz J., Żyluk A.: Podstawy eksploatacji statków powietrznych, tom 3. ITWL, Warszawa 2006. 4. Merkisz J., Galant M., Bieda M.: Analysis of operating instrument landing system accuracy under simulated conditions. Sci. J. Silesian Univ. Technol. Ser. Transp., vol. 94, 2017. 5. Pilot’s Operating Handbook Cessna 152. 6

. Abdulsamad, K. Leimbach et al. State of the Art and Simulation of Motion Cueing Algorithm for a Six Degree of Freedom Driving Simulator. – In: IEEE 17th International Conference on Intelligent Transportation System (ITSC), Qingdao, 2014, pp. 537-541. 8. Wang, J.-Z., Y. Tang, X.-L. Zhang. Proprioceptive Simulation Algorithm for the Driving Simulator System for Special Heavy Vehicles. – Transactions of Beijing Institute of Technology, Vol. 28 , 2008, No 8, pp. 670-673. 9. Jian, G. Research on Fidelity of Motion Cueing System in Flight Simulator. Ph. D. Dissertation, Harbin

coefficient determination and model simplification of submarine. Ocean Engineering, 154, 16–26. 23. Stewart D. (1966): A platform with six degrees of freedom . Aircraft Engineering and Aerospace Technology, 38(4), 30–35. 24. Yurt S. N., Ozkol I., Hajiyev C. (2004): Error analysis and motion determination of a flight simulator. Aircraft Engineering and Aerospace Technology, 76(2), 185–192. 25. Landry S. J., Jacko J. (2012): Pilot Procedure-Following Behavior during Closely Spaced Parallel Approaches. International Journal of Human-Computer Interaction, 28(2), 131