Please use this identifier to cite or link to this item: http://nopr.niscair.res.in/handle/123456789/42974
Title: Parallel Tuning of Fuzzy Tracking Controller for Deep Submergence Rescue Vehicle using Genetic Algorithm
Authors: Auxillia, D. Jeraldin
Keywords: Under water vehicle;Fuzzy logic controller;Genetic algorithm;Optimization;Trajectory tracking
Issue Date: Nov-2017
Publisher: NISCAIR-CSIR, India
Abstract: Deep Submergence Rescue Vehicle (DSRV) is an underwater vehicle designed for immediate rescue operation in the incident of a submarine mishap.  During this rescue operation, precise and dynamic trajectory tracking of DSRV is difficult due to poor visibility and  complex marine environment caused by unstable waves, winds etc. In this work a Genetic based Fuzzy Logic Controller (GAFLC) is designed to solve the trajectory tracking control problem of DSRV in the presence of unknown time varying wave disturbances.  In first step a conventional Fuzzy Logic Controller (FLC) is designed with fixed rule base and membership functions from expert’s knowledge and scaling factor chosen by trial and error.  In second step to enhance the trajectory tracking performance and to improve the system robustness to unstable wave disturbances the complete knowledge base of FLC is parameterized and optimized to find an optimal fuzzy controller without expert‘s knowledge. Genetic Algorithm (GA) is used to optimize the input and output membership functions, the rule base and the scaling factors of FLC simultaneously. Simulations are performed on four 2D reference trajectories corresponding to under water scenarios to demonstrate the effectiveness of the designed GAFLC in trajectory tracking and disturbance rejection.
Page(s): 2228-2240
URI: http://nopr.niscair.res.in/handle/123456789/42974
ISSN: 0975-1033 (Online); 0379-5136 (Print)
Appears in Collections:IJMS Vol.46(11) [November 2017]

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