Model-Based Optimal Control of a Small Remotely Operated Vehicle

Abstract

Remotely Operated Vehicles, ROVs, are useful devices that can greatly assist humans in the development deep-sea exploration and underwater tasks. These unmanned vehicles require human intervention for the realization of its underwater jobs and have the ability to carry multiple instruments, sensors and actuators according to the application. There are numerous commercial ROV platforms, ranging from inexpensive to very advanced and costly systems. Being an underactuated system, one of the most important factors in the development of a ROV is the design of its control system. Depending on the quality of the implemented control strategy, the functioning of the vehicle may or may not fail, or the accuracy with which its assignments are done may be seriously compromised. Different control strategies can be utilized for the stabilization and maneuvering of a ROV. The design of these strategies often require system parameter identification. Appropriate modeling and knowledge about the dynamic behavior of the system is essential for a successful parameter identification. One of the main parameters that must be identified is the drag coefficient of the ROV as it moves in the fluid. This parameter can be either experimentally measured, or estimated using the finite element method, to quantify the forces due to fluid-structure interaction. This work seeks the design and comparison of different advanced control techniques as applied to a small ROV. A commercial small ROV system has been chosen as the object of study and finite element simulations were carried out to estimate some of its mechanic parameters, using the commercial software COMSOL Multiphysics®. The nonlinear model of the system is developed and linearized to obtain its state space representation. The state space representation of the system is then used in the design of a LQR control system. The comparisons of the responses of the compensated systems allows assessing the suitability of the optimal control strategy for stabilization of ROVs.