An Open-Source Benchmark Simulator: Control of a BlueROV2 Underwater Robot

Abstract

This paper presents a simulation model environment for the popular and low-cost remotely operated vehicle (ROV) BlueROV2 implemented in Simulink™ which has been designed and experimentally validated for benchmark control algorithms for underwater vehicles. The BlueROV2 model is based on Fossen’s equations and includes a kinematic model of the vehicle, the hydrodynamics of vehicle and water interaction, a dynamic model of the thrusters, and, lastly, the gravitational/buoyant forces. The hydrodynamic parameters and thruster model have been validated in a test facility. The benchmark model also includes the ocean current, modeled as constant velocity. The tether connecting the ROV to the top-site facility has been modeled using the lumped mass method and is implemented as a force input to the ROV model. At last, to show the usefulness of the benchmark model, a case study is presented where a BlueROV2 is deployed to inspect an offshore monopile structure. The case study uses a sliding mode controller designed for the BlueROV2. The controller fulfills the design criteria defined for the case study by following the provided trajectory with a low error. It is concluded that the simulator establishes a benchmark for future control schemes for position control and trajectory tracking under the influence of environmental disturbances.

Disturbance Observer-Based Model Predictive Control for an Unmanned Underwater Vehicle (UUV)

“…The future work encompasses two primary aspects. Firstly, a comparative analysis can be conducted to assess the effectiveness and robustness of the proposed DOBMPC in relation to other robust controllers, such as SMC [35], which have the capability to adapt to complex operational environments. This comparison will provide valuable insights into the performance of the proposed approach.…”

Disturbance Observer-Based Model Predictive Control for an Unmanned Underwater Vehicle

“…The system process model f (x, τ, w) and the measurement model h(x) can be linearized by taking the partial derivatives of each to evaluate the state transition matrix F and the measurement matrix H at each operating point with Jacobian matrix. Equation (32) provides the state transition matrix F that captures the connection between the current state and the subsequent predicted state in a dynamic system. This matrix is derived using continuous-time t as a basis.…”

Dynamic robust path-following control of UVMS subject to manipulator disturbance

“…The modeling of the UVMS body adopts the η -ν Fossen formula recommended by the Society of Naval Architects and Marine Engineers (SNAME) [9], and the formula is as follows:…”