[PDF][PDF] Comparison of controllers design performance for underwater remotely operated vehicle (ROV) depth control

H Harun, AF Husni, MB Rusli… - International Journal of …, 2018 - researchgate.net
International Journal of Engineering & Technology, 2018researchgate.net
This paper presented controller designs utilized in controlling the ROV depth control system
which involved Single Input Fuzzy Logic Controller (SIFLC), Adaptive Neural Fuzzy
Inference System (ANFIS), Mamdani Fuzzy Logic Controller (M-FLC) and Proportional
Integrated Differential (PID) controller. The model of ROV was generate using MATLAB
System Identification Toolbox's to gain a transfer function representing the ROV model. This
ROV design focused on depth control. The main objective of this study was to analyze the …
Abstract
This paper presented controller designs utilized in controlling the ROV depth control system which involved Single Input Fuzzy Logic Controller (SIFLC), Adaptive Neural Fuzzy Inference System (ANFIS), Mamdani Fuzzy Logic Controller (M-FLC) and Proportional Integrated Differential (PID) controller. The model of ROV was generate using MATLAB System Identification Toolbox’s to gain a transfer function representing the ROV model. This ROV design focused on depth control. The main objective of this study was to analyze the performance of system response among the Controller designs. This controller was verified and validated in MATLAB/Simulink platform. The result showed the analysis performances of the system response in terms of rise time and percentage of overshoot.
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