1. bookVolumen 13 (2022): Heft 1 (January 2022)
Zeitschriftendaten
License
Format
Zeitschrift
eISSN
2336-3037
Erstveröffentlichung
16 Apr 2017
Erscheinungsweise
1 Hefte pro Jahr
Sprachen
Englisch
access type Uneingeschränkter Zugang

An Approach to Developing Mathematical Software of On-Board Helicopter Flight Simulator Decision Support System

Online veröffentlicht: 28 May 2022
Volumen & Heft: Volumen 13 (2022) - Heft 1 (January 2022)
Seitenbereich: 61 - 72
Eingereicht: 14 Feb 2022
Akzeptiert: 13 Apr 2022
Zeitschriftendaten
License
Format
Zeitschrift
eISSN
2336-3037
Erstveröffentlichung
16 Apr 2017
Erscheinungsweise
1 Hefte pro Jahr
Sprachen
Englisch
Abstract

The work explores methods and develops aids to improve a pilot flight training level using Full Flight Simulators. It examines their didactic advantages over real helicopters by implementing on-board intelligent decision support systems (IDSS). These simulation programs monitor actions of learner, find the best ways to correct errors and generate appropriate instructions. The training is carried out by reference point methods while the helicopter flight dynamics model simulates a flight and helps an instructor in parallel. Sufficiently simple and accurate model of helicopter flight dynamics was selected and tested to assess the proposed methods and aids. Our analysis introduces a functional structure of IDSS as an adaptive control system with a reference model. We further conducted a study on developing models, methods and means of automatic analysis, forecasting, optimization and correction of actions. Combining single-criteria conditional and vector optimization methods, we found out optimal flight parameters. The research findings revealed that the chosen optimization method requires too many system resources for the optimal solution to be found in a short time. The study thereby comes up with applying ANNs to solve this problem.

[1] Titov, A. (2012). Reference point method and its development in the “electronic instructor” (in russian). [Electronic version, http://www.aex.ru/fdocs/3/2012/5/11/21150/] Aviapanorama 2(92)-2012. Moscow. Search in Google Scholar

[2] Andrienko, O. Huchenko, M. Zinchenko, V. & Zhorniak, O. (2019). Software-hardware complex of qualification evaluation of Mi-171 helicopter simulator. Technical sciences and technologies. Chernihiv. nat. technologist un-t. - Chernihiv: ChNTU 3(17), 49-54. DOI: 10.25140/2411-5363-2019-3(17)-49-54.10.25140/2411-5363-2019-3(17)-49-54 Search in Google Scholar

[3] Trinon, H. (2019). Immersive technologies for virtual reality - Case study: flight simulator for pilot training. HEC-Ecole de gestion de l’Universite de Liege. Master en ingenieur de gestion, а finalite specialisee en Supply Chain Management and Business Analytics. From http://hdl.handle.net/2268.2/6443 Search in Google Scholar

[4] Williams, B. (2007). Microsoft® Flight Simulator as a Training Aid: A Guide for Pilots, Instructors, and Virtual Aviators. Search in Google Scholar

[5] Rong, J. Spaeth, T. & Valasek, J. (2005). Small Aircraft Pilot Assistant: Onboard Decision Support System for SATS Aircraft. Texas A&M University. DOI: 10.2514/6.2005-7382.10.2514/6.2005-7382 Search in Google Scholar

[6] Randleff, L.R. (2007) Decision Support System for Fighter Pilots Technical University of Denmark, Informatics and Mathematical Modelling, Building 321, DK-2800 Kongens Lyngby, Denmark, www.imm.dtu.dk Search in Google Scholar

[7] Turban, E. & Aronson, J.E. (2001) Decision Support Systems and Intelligent Systems, 6th edition. Prentice Hall, Upper Saddle River, NJ. Search in Google Scholar

[8] Makshanov, A.V., Zuravlev, A.E. & Tindikar L.N. (2016). Decision support systems (in russian). Educational edition. Lan Publishing. Search in Google Scholar

[9] Zingale, C. & Woroch, B. (2019). Air Traffic Control Decision Support Tool. Design and Implementation Handbook. DOT/FAA/TC-19/37 Federal Aviation Administration William J. Hughes Technical Center Atlantic City International Airport, NJ 08405. Search in Google Scholar

[10] Bect, P., Simeu-Abazi, Z. & Maisonneuve, P.L. (2015). Diagnostic and decision support systems by identification of abnormal events: Application to helicopters. Aerospace Science and Technology. DOI: 46. 10.1016/j.ast.2015.07.024. Search in Google Scholar

[11] Rädsch, T., Reuter-Oppermann, M. & Richards, D. (2021). Towards a Machine Learning-based Decision Support System for Dispatching Helicopters in New Zealand. DOI: 10.24251/HICSS.2021.210.10.24251/HICSS.2021.210 Search in Google Scholar

[12] Khalin V.G. (2019). Decision support systems (in russian). Moscow. Publishing house Yurayt. Search in Google Scholar

[13] Romasevich, V.F. (1982). Aerodynamics and flight dynamics of helicopters (in russian). Moscow. Military publishing house of the Ministry of Defense of the USSR. Search in Google Scholar

[14] National technical standard GOST 20058-80 (in Russian). Aircraft dynamics in atmosphere. Terms, definitions and symbols. Search in Google Scholar

[15] Ground and aviation training course for army aviation cadets (KNLP AA-2004). Ministry of Defense of Ukraine. Kharkiv, 2004. Search in Google Scholar

[16] U.S. Department of Transportation, Federal Aviation Administration, Flight Standards Service. (2008). Aviation Instructor’s Handbook (FAA-H-8083-9). From https://www.leteckylekar.cz/images/faa-h-8083-9a.pdf Search in Google Scholar

[17] Pupkov, K.A. & Yegupov, N.D. (2002) Robust, neuro-fuzzy and adaptive control methods (in Russian). Moscow, MSTU im. Bauman. Search in Google Scholar

[18] Mykel, J., Kochenderfer, T. & Wheeler, A. (2019) Algorithms for Optimization. The MIT Press. Cambridge, Massachusetts. London, England. Search in Google Scholar

[19] Kasim, M.M. (2020). On the Practical Consideration of Evaluators’ Credibility in Evaluating Relative Importance of Criteria for Some Real-Life Multicriteria Problems: An Overview, Multicriteria Optimization - Pareto-Optimality and Threshold-Optimality, Nodari Vakhania and Frank Werner, IntechOpen, DOI: 10.5772/intechopen.92541. Available from: https://www.intechopen.com/chapters/72225 Search in Google Scholar

[20] Lukashin Y.U.P. (2003) Adaptive methods of short-term forecasting of time series (in Russian). Moscow. Finance and statistics. Search in Google Scholar

Empfohlene Artikel von Trend MD

Planen Sie Ihre Fernkonferenz mit Scienceendo