Speed Scheduling of Autonomous Railway Vehicle Control System using Neuro-Fuzzy System
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Full Text(PDF, 3000) PP.
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Author(s) |
Aiesha Ahmad, M.Saleem Khan, Khalil Ahmed, Nida Anwar and Atifa Athar |
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KEYWORDS |
Autonomous Railway Vehicle, Control System, Environment Monitoring, Learning and Adaptation, Neuro-Fuzzy System, Railway Track System, Speed Scheduling
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ABSTRACT |
This paper presents the speed scheduling system of autonomous railway vehicles using neuro-fuzzy system. Speed maintaining and scheduling system is considered integral part for successful development of autonomous railway vehicle control system. This work focuses on development of intelligent speed scheduling system to successfully cope with constraint of different conditions by improving performance and stability as compared to existing control systems of railway vehicles. This intelligent speed scheduling system has ability to learn, take decision and act according to hard conditions; junction track information (JTI), crossing gate information (CG) and track clearance (TCL), and flexible conditions; vehicle tilting (VT), track condition (TC) and environment monitoring (EM), uses neuro-fuzzy system (NFS) comprising main features of fuzzy inference system (FIS) and artificial neural network (ANN). Artificial neural network (ANN) and fuzzy inference system (FIS) are used to solve complex real time speed scheduling problems intelligently by learning, adaptation and human knowledge incorporation. The proposed speed scheduling system learns and adapts automatically under uncertain situations of railway track system. This helps to maintain successfully the speed of railway vehicles with environment monitoring, time scheduling and minimizes the risk of overturning.
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References |
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