Toolset for Construction and Verification of Rules for Spacecraft's Autonomous Decision Making
Pages 811 - 818
Abstract
Dependability of control system is one of the most complex problems in space projects. Decision making in case of contingencies is a non-trivial process requiring some "intelligence". We can implement the "onboard intelligence" in different ways. The most common approach involves its implementation in the source code of the flight control software. The approach presented in the paper uses an onboard real-time decision making system. The decision making rules can be added or updated from Earth by radio channel. Currently, the rules should be specified in a table form, leading to misunderstandings in project team and errors. The improved approach provides the special toolset including, visual constructor of rules and support of rules' verification. The proposed approach allows the engineers to define visually construct and update the decision making rules without programming background easily. The toolset prototype was positively evaluated at enterprise JSC Information Satellite Systems, Russia.
References
[1]
Kozlov DI, Anshakov GP, Mostovoy YaA. Control of Earth Observation Satellites: Computer Technologies. Moscow: Mashinostroenie; 1998. (In Russian).
[2]
Kirilin AN, Akhmetov RN, Sollogub AV, Makarov VP. Methods for Survivability of Low-Orbit Earth Observation Satellites: Mathematical Modelling, Computer Technologies. Moscow: Mashinostroenie; 2010. (In Russian).
[3]
R.N. Akhmetov, V.P. Makarov, A.V. Sollogub, Principles of the Earth Observation Satellites Control in Contingencies, Information and Control Systems, 1 (2012) 16-22.
[4]
Eickhoff, J. Onboard Computers, Onboard Software and Satellite Operations. An Introduction. Heidelberg: Springer-Verlag; 2012.
[5]
V.V. Khartov, Autonomous Control of Communication and Navigation Spacecraft, Aviakosmicheskoe priborostroenie (Aerospace Instrument-Making), 6 (2006) 12-23.
[6]
S. Watanabe, Knowing and Guessing, Wiley, New York, 1969.
[7]
Krasner S, Bernard DE. Integrating Autonomy Technologies into an Embedded Spacecraft System-Flight Software System Engineering for New Millennium. Proc. of the IEEE Aerospace Conference Snowmass, CO, USA; 1997.
[8]
Luger GF, Stubblefield WA. Artificial Intelligence and the Design of Expert Systems. Redwood City: Benjamin/Cummings Publishing Co.; 1989.
[9]
Tomayko JE. Computers in Space: Journeys with NASA. Indianapolis: Alpha Books; 1994.
[10]
Tomayko JE. Computers Take Flight: A History of NASA's Pioneering Digital Fly-By-Wire Project. Washington, D.C.: NASA History Office; 2000.
[11]
L.I. Koczela, G.I. Burnett, Advanced Space Missions and Computer Systems, IEEE Trans. on Aerospace and Electronics Systems, AES-4 (1968) 456-467.
[12]
B. Hayes-Roth, An Architecture for Adaptive Intelligent Systems, Art Int, 72 (1995) 329-365.
[13]
Grabot B, Geneste L, Dupeux A. Experimental Design, Expert System and Neural Network Approaches: Comparison for the Choice of Parameters, Proc. International Conference on Systems, Man and Cybernetics, 'Systems Engineering in the Service of Humans', Le Touquet, France, vol. 4, p. 15-20; 1993.
[14]
Nakamatsu K, LC Jain, Editors. The Handbook on Reasoning-Based Intelligent Systems. World Scientific; 2013.
[15]
Smith RK, Muscettola N. Knowledge Acquisition for the Onboard Planner of an Autonomous Spacecraft. Technical Report - American Association for Artificial Intelligence WS; 48-57; Knowledge Engineering and Acquisition for Planning: Bridging Theory and Practice by AAAI Press; 1998.
[16]
Lemos JM, Neves-Silva R, Igreja JM. Adaptive Control of Solar Energy Collector Systems. Springer International Publishing; 2014.
[17]
Pospelov DA. Situational Control: Theory and Practice (M. N. Golovin and N. Grunewald, Trans.). Columbus: Batelle Memorial Institute; 1986.
[18]
Koltashev AA. Effective Technology of Lifecycle Management of Communication and Navigation Satellite's Onboard Software. Aviakosmicheskoe priborostroenie (Aerospace Instrument-Making) 2006; 12:24-31, (In Russian).
[19]
E.V. Kochura, Development of Macro Programs for Integrated Control of Spacecraft, Vestnik SibAU (Bulletin of Siberian State Aerospace University), 1 (2011) 105-107.
[20]
Parondzhanov VD. Druzhelyubnye algoritmy, ponyatnye kazhdomu. Kak uluchshit' rabotu uma bez lishnih hlopot (Friendly algorithms understandable for everybody. Algorithms without programmers). Moscow: DMK Press; 2010. (In Russian).
[21]
Tiugashev AA. Graphical Programming Languages and Their Application in Real-Time Control Systems. Samara: Samara Centre of the Russian Academy of Sciences; 2009. (In Russian).
[22]
Tyugashev AA, Ermakov IE, Ilyin II. Ways to Get More Reliable and Safe Software in Aerospace Industry. Proc. Program Semantics, Specification and Verification: Theory and Applications (PSSV 2012), July 1-2, 2012 in Nizhni Novgorod, Russia, p. 121-926.
[23]
P.P. Ruiz, B.K. Foguem, B. Grabot, Generating Knowledge in Maintenance from Experience Feedback, Know Bas Sys, 68 (2014) 4-20.
[24]
Drucker J. Graphesis: Visual Forms of Knowledge Production. Boston: Harvard University Press; 2014.
[25]
Chein M, Mugnier ML. Graph-Based Knowledge Representation: Computational Foundations of Conceptual Graphs, Springer-Verlag Berlin Heidelberg; 2008.
[26]
M.J. Eppler, R.A. Burkhard, Visual Representations in Knowledge Management: Framework and Cases, J of Know Manag, 11 (2007) 112-122.
[27]
Nobécourt J, Biébow B. Mdws: A Modeling Language to Build a Formal Ontology in Either Description Logics or Conceptual Graphs, Knowledge Engineering and Knowledge Management Methods, Models, and Tools, Vol. 1937, Lecture Notes in Computer Science, Springer Berlin Heidelberg, p. 57-64; 2002.
[28]
Pfeiffer HD, Hartley RT. Visual CP Representation of Knowledge. Supplemental Proceedings of the 8th International Conference on Conceptual Structures, ICCS 2000, Darmstadt, Germany; 2000.
[29]
Parondzhanov VD, Trunov YuV. Control System of "Fregat" Versatile Space Tug. Vestnik NPO imeni S.A. Lavochkina. Cosmonautics and Rocket Engineering (Bulletin of Lavochkin Space Center) 2014; 1(22): 16-25. (In Russian).
[30]
Martin J. Application Development without Programmers. PTR Upper Saddle River: Prentice-Hall; 1982.
[31]
Kalentyev AA, Tiugashev AA, Bogatov AV, Shulyndin AV. Visual Toolset for Real-Time Onboard Programs Verification Support. Proc. Program Semantics, Specification and Verification: Theory and Applications (PSSV 2011). St.Petersburg, Russia; p.101-9; 2011.
Recommendations
Validation and verification of decision making rules
A methodology for the validation and verification of decision making rules is presented. The methodology addresses the general problem of detecting problematic cases in a set of rules expressed as statements in formal logic. This representation of the ...
The design of AHPEC in web-based decision support system for making decision
AIC'10/BEBI'10: Proceedings of the 10th WSEAS international conference on applied informatics and communications, and 3rd WSEAS international conference on Biomedical electronics and biomedical informaticsThis paper presents the architecture of the WDSS using AHPEC for making decision. The WDSS-AHPEC involves client, user interface, server, web server, database, and DSS model. The DSS model in this study is using AHPEC method. In applying AHPEC, it ...
Eliciting Predictions and Recommendations for Decision Making
When making a decision, a decision maker selects one of several possible actions and hopes to achieve a desirable outcome. To make a better decision, the decision maker often asks experts for advice. In this article, we consider two methods of acquiring ...
Comments
Information & Contributors
Information
Published In
Publisher
Elsevier Science Publishers B. V.
Netherlands
Publication History
Published: 01 October 2016
Author Tags
Qualifiers
- Research-article
Contributors
Other Metrics
Bibliometrics & Citations
Bibliometrics
Article Metrics
- 0Total Citations
- 0Total Downloads
- Downloads (Last 12 months)0
- Downloads (Last 6 weeks)0
Reflects downloads up to 20 Jan 2025