학술논문

Robust Nonlinear Model Predictive Control of an Autonomous Launch and Recovery System
Document Type
Periodical
Source
IEEE Transactions on Control Systems Technology IEEE Trans. Contr. Syst. Technol. Control Systems Technology, IEEE Transactions on. 31(5):2082-2092 Sep, 2023
Subject
Signal Processing and Analysis
Communication, Networking and Broadcast Technologies
Computing and Processing
Robotics and Control Systems
Marine vehicles
Task analysis
Computational modeling
Safety
Predictive control
Hydrodynamics
Trajectory
Launch and recovery (L&R)
model predictive control
safety enhancement
Language
ISSN
1063-6536
1558-0865
2374-0159
Abstract
Launching and recovering a lifeboat from a mother ship is a critical task for rescuing people in high sea states, which can be dangerous to both the mother ship crew and lifeboat personnel. A reliable and efficient control system is crucial to reducing the risk but has not been developed to a mature stage to establish an autonomous launch and recovery system (LARS). A successful manually controlled launch and recovery (L&R) mission relies on empirically assessing the risk and planning the operation ahead of initiating the process. This article proposes a control scheme for the LARS which executes the task in two stages: the L&R risk assessment is conducted in the first stage before hoisting the lifeboat; then in the second stage, input signals are manipulated to accomplish the task once the mission is identified to be safe. We propose a robust tube-based model predictive control (TMPC) law in both stages. It can explicitly consider uncertainties in the LARS model and guarantee constraint satisfaction by bounding possible system trajectories in a predefined tube. Hence degradation of control performance caused by inaccurate system modeling can be minimized to improve the operation safety level of the entire process. The performance of the proposed control scheme is demonstrated by numerical simulations.