Open AccessControl system design for steering and depth subsystems of autonomous underwater vehicle
Author(s) -
Sherif Mostafa,
Yehia Z. Elhalwagy,
Mohammed A. H. Abozied,
Ahmed M. Kamel
Publication year - 2021
Publication title -
journal of physics. conference series
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.21
H-Index - 85
eISSN - 1742-6596
pISSN - 1742-6588
DOI - 10.1088/1742-6596/1721/1/012031
Subject(s) - control theory (sociology) , waypoint , pid controller , control engineering , autopilot , linear quadratic regulator , nonlinear system , underwater , engineering , linearization , controller (irrigation) , computer science , control (management) , temperature control , oceanography , physics , quantum mechanics , artificial intelligence , geology , aerospace engineering , agronomy , biology
This work seeks to propose the development of a classical-optimized control design scheme for the steering and depth subsystems of autonomous underwater vehicle. Linearization methodological approach is carried out for acquiring the transfer functions to design the convenient P/PD/PID controllers where the gains are optimally adjusted utilizing a graphical tuning technique in LabVIEW. A low pass filter with additional alpha tuning parameter is combined with the derivative action to suppress the expected oscillations entirely. Furthermore, a comparative analysis study with linear quadratic regulator optimal control is established for testing and evaluating the suggested design approach. The effectiveness of the addressed controller strategy is appraised for compensating and rejection of several uncertainties such as fin saturation, angle limitation and sensor measurements noise as they are potentially affecting the system response. The validity of the linearized classical-optimized control design is substantiated with the nonlinear underwater vehicle model through a waypoint guidance scenario under LabVIEW simulation platform. The results revealed a significant improvement in transient and steady state responses and a remarkable enhanced stability for tracking the desired path to different designated waypoints.