Open AccessStabilizing and Controlling the Altitude and Attitude of Remotely Operated Underwater Fishing Drone
Author(s) -
Fahad Farooq
Publication year - 2021
Publication title -
quaid-e-awam university research journal of engineering science and technology
Language(s) - English
Resource type - Journals
eISSN - 2523-0379
pISSN - 1605-8607
DOI - 10.52584/qrj.1902.11
Subject(s) - control theory (sociology) , pid controller , robustness (evolution) , computer science , convergence (economics) , lyapunov function , fishing , drone , stability (learning theory) , simulation , engineering , control engineering , control (management) , ecology , artificial intelligence , economics , physics , temperature control , biochemistry , chemistry , genetics , nonlinear system , quantum mechanics , machine learning , biology , gene , economic growth
Fishing is one of the most intense and time-consuming occupations. Sometimes it's hard to find a healthy fish population and fishermen to travel far offshore for this purpose and it's sometimes dangerous in bad weather conditions. The study focuses on controlling and stabilizing the altitude and attitude of the fishing drone. This manuscript designs dual control based on model adaptive control (MAC) with Proportional integral derivative (PID). It also uses an integral as the feedback. MAC deals with the disturbances and PID tunes the systems adaptive gain. Furthermore, the Lyapunov stability criterion helps in maintaining the stability of the system. The feedback removes the steady-state error and improves the convergence rate. The simulation results verify the accuracy and effectiveness of the designed scheme. The designs scheme shows high convergence, low steady-state error, and better robustness.