METHOD OF DETERMINATION CRITERIA FOR SAFE SPEED OF VESSELS WHILE NAVIGATING THE DNIPRO RIVER
DOI:
https://doi.org/10.26906/SUNZ.2023.4.034Keywords:
vessel, safe speed, motion control system, ship control system, formalisation, data collection and processing, ship motion model, methodology, fuzzy logic, fuzzy set theory, agent, agent system, multi-agent system, measuring complex, ship condition, ship navigation conditions, data library, real time, decision makingAbstract
The aim of this paper is to build the architecture of the ship motion control system based on modification of the principles of building the model of the ship motion control system itself using new approaches to formalizing the processes of information collection and processing. This goal is achieved by analyzing the main options for building ship motion models (SMM), developing a methodology for its formation based on stored information about ship motion, synthesizing SMM using fuzzy logic and assessing the quality of their work, and building an agent-based model of ship motion control based on the developed SMM. The most significant result is the development of the structure of the agent system for processing the output data from the measuring complex and the mathematical description of this system by agents, environmental objects and events occurring in it. In addition, the elements of the system are interconnected by the reaction of the environment to the action or inaction of agents, which are considered as the laws of the system's functioning. The significance of the obtained results lies in the development of the methodology and structure of the system for forming a ship motion model, which is distinguished by the use of the results of measurements of the ship's states and its navigation conditions during regular voyages and the formation of a library on this basis. The peculiarity of the obtained results is the accumulation of data measured after the assessment of their novelty in a structured library and their periodic use for model refinement. The proposed structure of the model library and the source data base are similar in structure and contain two sections - ship states and navigation conditions, which directly affects the methodology for selecting the required model from the library. The difference from the known works lies in the structuring of navigation conditions based on the provisions of fuzzy set theory, which made it possible to select models that are most suitable for the current situation without using additional maneuvering to form them. To implement multi-agent systems operating in real time, it is proposed to develop a module for decision-making by an agent and to implement goal-setting functions during the implementation of decisions. The proposed approaches allow improving the quality of the formal description of the tasks to be solved, formalizing the processes of collecting and processing information about the ship's state and navigation conditions, and implementing the architecture of the ship's control system for different conditions.Downloads
References
Про затвердження Правил судноплавства на внутрішніх водних шляхах України // Наказ міністерства транспорту України від 16.02.2004 р. №91 (зі змінами) // https://www.google.com/ (Дата звернення 06.10.23).
Правила плавания по внутренним водным путям Украины // https://www.google.com (Дата звернення 06.10.23).
Alur, R. A theory of timed automata / R. Alur, D. L. Dill // Theoretical Computer Science. — 1994. — Vol. 126, no. 2. — Pp. 183–235.
Борсук С.П. Ергономічні основи проактивної кваліметрії закономірностей прояву людського чинника в аеронавігаційних системах : дис. ... кандидата техн. наук 05.01.04 / Борсук Сергій Павлович. Харків, 2019. – 378 с.
Вагущенко Л.Л. Поддержка решений по расхождению с судами / Л.Л. Вагущенко. – Одесса: Феникс, 2010. – 229 с.
Тихонов І.В. Методологічні основи поліергатичного забезпечення навігації та управління рухом водних транспортних засобів (цільова технологія безпеки) : дис. ... канд. техн. наук 05.22.13 / Тихонов Ілля Валентинович. Київ, 2018. – 441 с.
Alur, R. Timed automata // Proc. 11th International Conference on Computer Aided Verification. — London (UK): SpringerVerlag, 1999. — Pp. 8–22.
Andreka, H. Handbook of Philosophical Logic / H. Andreka, I. Nemeti, I. Sain // Handbook of Philosophical Logic / Ed. by D. Gabbay. — Kluwer, 1997.
Antoniotti, M. Synthesis and verification of discrete controllers for robotics and manufacturing devices with temporal logic and the Control-D system: Ph.D. thesis / New York University. — New York, NY, USA: New York University, 1995.
AUV local path planning based on virtual potential field / D. Fuguang // IEEE International Conference Mechatronics and Automation, 2005. Т. 4. — 2005. — С. 1711—1716.
Aziz, A. BDD variable ordering for interacting finite state machines // Proc. 31st annual conference on Design automation. — San Diego (USA): ACM Press, 1994. — Pp. 283–288.
Bacchus, F. Planning for temporally extended goals / F. Bacchus, F. Kabanza // Annals of Mathematics and Artificial Intelligence. — 1998. — Vol. 22, no. 1-2. — Pp. 5–27.
Badler N.I., Reich B.D., Webber B.L. Towards personalities for animated agents with reactive and planning behaviors // Creating Personalities for Synthetic Actors: Towards Autonomous Personality Agents. — Berlin, Heidelberg: Springer Berlin Heidelberg, 1997. — С. 43—57. — ISBN 978-3- 540-68501-2.
Baeten, J. C. M. A brief history of process algebra / J. C. M. Baeten // Theor. Comput. Sci. — 2005. — Vol. 335, no. 2-3. — Pp. 131–146.
Baier, C. Approximate symbolic model checking of continuous-time markov chains // Proc. 10th International Conference on Concurrency Theory. — London (UK): Springer-Verlag, 1999. — Pp. 146–161.
Beer R.D., Gallagher J.C. Evolving dynamical neural networks for adaptive behavior // Adaptive behavior. — 1992. — Т. 1, № 1. — С. 91—122.
Bel-Enguix G., Jimenez-Lopez M.D. Agent-environment Interaction in a Multiagent System: A Formal Model // Proceedings of the 9th Annual Conference Companion on Genetic and Evolutionary Computation. — London, United Kingdom : ACM, 2007. — С. 2607—2612. — (GECCO ’07). — ISBN 978-1- 59593-698-1. 107.
Berg J. van den, Lin M.C., Manocha D. Reciprocal Velocity Obstacles for RealTime Multi-Agent Navigation // IEEE INTERNATIONAL CONFERENCE ON ROBOTICS AND AUTOMATION. — IEEE, 2008. — С. 1928—1935.
Bonabeau E., Dorigo M., Theraulaz G. Swarm Intelligence. From Natural to Artificial Systems. — Oxford University Press, 1999. — 322 с. — (Santa Fe Institute Studies on the Sciences of Complexity). — ISBN 0195131584.
Bonet, B. Heuristic search planner 2.0 / B. Bonet, H. Geffner // The AI Magazine. — 2001. — Vol. 22, no. 1. — Pp. 77–80.
Bonet, B. Planning as heuristic search / B. Bonet, H. Geffner // Artificial Intelligence. — 2001. — Vol. 129, no. 1-2. — Pp. 5–33.
Borgo, S. Coalitions in action logic // Proc. Twentieth International Joint Conference on Artificial Intelligence. — Hyderabad (India): 2007. — January. — Pp. 1822–1827.
Brand, D. On communicating finite-state machines / D. Brand, P. Zafiropulo // J. ACM. — 1983. — Vol. 30, no. 2. — Pp. 323–342.
Bratman, M. E. Intention, plans, and practical reason / M. E. Bratman. — Cambridge, MA: Harvard University Press, 1987.
Bryant, R. E. Symbolic boolean manipulation with ordered binary-decision diagrams / R. E. Bryant // ACM Computing Surveys. — 1992. — Vol. 24, no. 3. — Pp. 293–318.
Bryant, R. E. Graph-based algorithms for boolean function manipulation / R. E. Bryant // IEEE Transactions on Computers. — 1986. — Vol. C-35, no. 8. — Pp. 677–691.
