Journal
IEEE ACCESS
Volume 8, Issue -, Pages 108835-108846Publisher
IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/ACCESS.2020.3001626
Keywords
Collision avoidance; Heuristic algorithms; Marine vehicles; Fuzzy logic; Adaptive systems; Real-time systems; ASV collision avoidance; fuzzy logic; case base reasoning; input saturation
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Funding
- National Natural Science Foundation of China [61873071, 51911540478, G61773015]
- Key Research and Development Plan of Shandong Province [2019JZZY020712]
- Natural Science Foundation of Shandong Jiaotong University [Z201631]
- Shandong Jiaotong University
- Startup Foundation of Scientific Research
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Numerous researches have been done to develop ASV (Autonomous Surface Vessel) collision avoidance systems. Most of the systems used static methods but did not apply a knowledge base where solutions can be reused and adapted to solve a new case. In this paper, an algorithm of autonomous collision avoidance is proposed considering steering dynamic for ASV. The process of this learning method is to recall the FCBR (Fuzzy Case Base Reasoning) containing basic expert knowledge in the form of stored cases. The solutions will be retrieved from the knowledge base to find a NH (New Heading) command for collision avoidance. Moreover, to execute the NH, a design of adaptive fuzzy ASV heading control system based on command filter is conducted considering the input saturation constraints and external disturbances. T-S fuzzy logic is employed to approximate nonlinear uncertainties existing in the heading control system adopting the MLP (Minimal Learning Parameter) technique. Finally, simulations prove that the method is effective to retrieve the past similar cases for the new collision avoidance situation and give its solution for ASV to track adjusted heading.
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