SYSTEM IDENTIFICATION (SI) MODELLING, CONTROLLER DESIGN AND HARDWARE TESTING FOR VERTICAL TRAJECTORY OF UNDERWATER REMOTELY OPERATED VEHICLE (ROV)

Underwater remotely operated vehicles (ROV) are important in marine industries to accomplish underwater exploration and surveying. The underwater environment makes it hard for ROV operators to control the manipulator while holding position simultaneously. This led to modelling and controller design for the vertical trajectory of ROV. In this paper, the System Identification (SI) modeling technique was used to model the vertical trajectory of the ROV. Then, the Proportional, Integral, and Derivative (PID) controller was implemented to control the trajectory. The SI modelling technique was used as it estimates the model based on the input and output relationship. MATLAB SI toolbox was used as the analytical software. Step and multiple step inputs were given to the system and the responses were recorded. The model with the best fit of 84.7% was selected and verified by comparing with actual output. The model response was then analyzed and the PID controller was implemented. The actual model had high percent overshoot (%OS) and steady state error (SSE). The PID implementation successfully reduced the %OS and eliminated the SSE. ABSTRAK: Kenderaan bawah air kendalian jauh (ROV) adalah penting dalam industri marin bagi melaksanakan penerokaan dan pemerhatian bawah air. Persekitaran dalam air menyukarkan pengendali ROV bagi memanipulasi manipulator sambil memastikan kedudukan ROV secara serentak. Ini membawa kepada pemodelan dan mereka bentuk kawalan pergerakan menegak bagi ROV. Kajian ini menggunakan teknik pemodelan Sistem Pengenalan (SI) bagi memodelkan pergerakan menegak ROV. Kemudian, kawalan seimbang, menyeluruh dan terbitan (PID) dilaksanakan bagi mengawal trajektori. Teknik pemodelan SI digunakan kerana ia menganggarkan model berdasarkan kemasukan dan keluaran. Aplikasi MATLAB SI digunakan sebagai perisian analisis. Masukan satu langkah dan berbilang kali masukan telah dijalankan dan respons sistem direkodkan. Model yang paling sesuai mencapai 84.7% dipilih dan disahkan dengan perbandingan nilai keluaran sebenar. Respons model kemudiannya dianalisis dan kawalan PID dilaksanakan. Model sebenar mempunyai peratusan tinggi melampaui (%OS) dan ralat keadaan stabil (SSE). Pelaksanaan PID telah berjaya mengurangkan %OS dan menghapuskan SSE.