@article{MAKHILLIJEPE202115525342,
    title = {Remotely Operated Underwater Vehicle Depth Control with New Lambda (λ) Tuning
Approach of Single Input Fuzzy Logic using Gradient Descent Algorithm and Particle Swarm
Optimization},
    journal = {International Journal of Electrical and Power Engineering},
    volume = {15},
    number = {5},
    pages = {43-51},
    year = {2021},
    issn = {1990-7958},
    doi = {ijepe.2021.43.51},
    url = {https://makhillpublications.co/view-article.php?issn=1990-7958&doi=ijepe.2021.43.51},
    author = {Mustefa},
    keywords = {Remotely operated vehicle,fuzzy logic controller,single input fuzzy logic,particle swarm optimization,gradient descent algorithm},
    abstract = {Underwater ROV is an important in underwater
industries as well as safety purpose. It can dive deeper
than human and can replace human in hazard underwater
environment. ROV depth control is difficult due to
hydrodynamic of the ROV itself and underwater
environment. Overshoot in the depth control may cause
damage to the ROV and its investigation location. This
paper presenting a new tuning approach of SIFLC with
GDA and PSO implementation for ROV depth control.
The ROV was modelled using system identification to
simulate the depth system. PID controller was applied to
the model as a basic controller. SIFLC was then
implemented in three tuning approach which are heuristic,
GDA and PSO. The output transient was simulated using
MATLAB Simulink and the percent overshoot (OS), time
rise (Tr) and settling time (Ts) of the systems without and
with controllers were compared and analysed. The result
shows that SIFLC GDA output has the best transient
result at 0.1021% (OS), 0.7992s (Tr) and 0.9790s (Ts).}
    }