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Robust-adaptive dynamic programming-based time-delay control of autonomous ships under stochastic disturbances using an actor-critic learning algorithm

Abstract

This paper proposes a hybrid robust-adaptive learning-based control scheme based on Approximate Dynamic Programming (ADP) for the tracking control of autonomous ship maneuvering. We adopt a Time-Delay Control (TDC) approach, which is known as a simple, practical, model free and roughly robust strategy, combined with an Actor-Critic Approximate Dynamic Programming (ACADP) algorithm as an adaptive part in the proposed hybrid control algorithm. Based on this integration, Actor-Critic Time-Delay Control (AC-TDC) is proposed. It offers a high-performance robust-adaptive control approach for path following of autonomous ships under deterministic and stochastic disturbances induced by the winds, waves, and ocean currents. Computer simulations have been conducted under two different conditions in terms of the deterministic and stochastic disturbances and all simulation results indicate an acceptable performance in tracking of paths for the proposed control algorithm in comparison with the conventional TDC approach.

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Category:
Articles
Type:
artykuły w czasopismach
Published in:
JOURNAL OF MARINE SCIENCE AND TECHNOLOGY no. 26, pages 1262 - 1279,
ISSN: 0948-4280
Language:
English
Publication year:
2021
Bibliographic description:
Esfahani H. N., Szłapczyński R.: Robust-adaptive dynamic programming-based time-delay control of autonomous ships under stochastic disturbances using an actor-critic learning algorithm// JOURNAL OF MARINE SCIENCE AND TECHNOLOGY -Vol. 26, (2021), s.1262-1279
DOI:
Digital Object Identifier (open in new tab) 10.1007/s00773-021-00813-1
Sources of funding:
  • Statutory activity/subsidy
Verified by:
Gdańsk University of Technology

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