Result: Robust optimal control of a nonlinear surface vessel model with parametric uncertainties

Title:
Robust optimal control of a nonlinear surface vessel model with parametric uncertainties
Authors:
Jambak, Ahmad Irham, Bayezit, Ismail
Source:
Brodogradnja, Vol 74, Iss 3, Pp 131-143 (2023)
Brodogradnja : An International Journal of Naval Architecture and Ocean Engineering for Research and Development
CODEN BRODBA
Volume 74
Issue 3
Publisher Information:
Faculty of Mechanical Engineering and Naval Architecture, Univ. of Zagreb, 2023.
Publication Year:
2023
Subject Terms:
Optimization, Artificial intelligence, Ship Motion Prediction, Naval architecture. Shipbuilding. Marine engineering, VM1-989, Parametric model, Ocean Engineering, Control (management), 02 engineering and technology, Process Fault Detection and Diagnosis in Industries, Quantum mechanics, 0201 civil engineering, optimal control, Engineering, Hydrodynamic Optimization, Control theory (sociology), FOS: Mathematics, Bisection method, Biology, Hydrodynamic Analysis of Ship Behavior and Performance, Physics, Controller (irrigation), Mathematical optimization, Statistics, Computer science, Agronomy, Process (computing), parametric uncertainty, Operating system, autonomous surface vessel, autonomous marine vehicle, Model Predictive Control in Industrial Processes, Control and Systems Engineering, Parametric statistics, Physical Sciences, Ship Maneuvering, Nonlinear system, optimization, robust control, Robust Control, Mathematics
Document Type:
Academic journal Article<br />Other literature type
File Description:
application/pdf
ISSN:
1845-5859
0007-215X
DOI:
10.21278/brod74307
DOI:
10.60692/c0qyb-we432
DOI:
10.60692/p3yqf-k6747
Access URL:
https://doaj.org/article/c437c58d06f54240ac5eb423c48f37bf
Accession Number:
edsair.doi.dedup.....22603ea32391521ab036d60844c8e6a3
Database:
OpenAIRE

Further Information

This paper presents a fast alternative optimization method for developing a reliable optimal controller that can handle system model parameter uncertainties. The source of uncertainty in this study is identified as hydrodynamic coefficients, which are prone to errors due to the challenges involved in obtaining accurate values. The proposed optimization method utilizes a complex nonlinear ship model provided by Maneuver Modelling Group (MMG) as the reference for the ship motion model. The optimization process is divided into two stages: a blind search followed by bisection optimization, to obtain a robust optimal controller. To demonstrate the effectiveness of the proposed approach, system response analysis and practical tests were performed on Step, M-Turn, and Doublet maneuvers. The results show that the controller parameters obtained from the proposed optimization method are capable of achieving high success rates in controlling a system with uncertain parameters.