Output feedback motion control system for observation class ROVs based on a high-gain state observer: Theoretical and experimental results

Fernandes, Daniel de Almeida; Sørensen, Asgeir J.; Pettersen, Kristin Y.; Donha, Décio Crisol

doi:10.1016/j.conengprac.2014.12.005

Cited by 70 publications

(36 citation statements)

References 37 publications

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“…The four DoF MCS used to carry out the simulation was that reported in Fernandes et al (2015), with the guidance subsystem built upon the just mentioned path generation scheme. The simulation was based on recursive use of the advanced version of the RM that is described in Subsection 2.2.…”

Section: Path Generation: Simulation Resultsmentioning

confidence: 99%

“…The references are meant to be employed in high-performance Motion Control Systems (MCSs) with trajectory tracking and Dynamic Positioning (DP) capabilities, e.g. Fernandes et al (2015), Omerdic et al (2012), Sørensen et al (2012), Caccia (2006), and Hsu et al (2000). Although this work focuses on (typically) fully-actuated Unmanned Underwater Vehicles (UUVs) such as ROVs, some of the ideas presented herein can be adapted to be used as a means of also guiding the motion of (typically) underactuated marine crafts, e.g.…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Path Generation for High-Performance Motion of ROVs Based on a Reference Model

Fernandes¹,

Sørensen²,

Donha³

2015

MIC

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This paper deals with the generation of sufficiently smooth position, velocity, and acceleration references for guiding the motion of an ROV along purposefully defined curvature-continuous paths in automated missions. The references are meant to be employed in high-performance trajectory tracking and dynamic positioning applications. The path planning problem is not in the scope of this work. A reference model that synthesises references concerning a single Degree-of-Freedom (DoF) motion is initially described. Then, the use of the synthesised references as the parametrisation for other references concerning multiple DoF motion along curvature-continuous paths is exploited. Results from computer simulations and full-scale sea trials, both based on the NTNU's ROV Minerva, are presented and discussed.Keywords: Guidance system, Path generation, Reference model, ROV, Trajectory tracking. List of acronyms and abbreviations

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Section: Path Generation: Simulation Resultsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Path Generation for High-Performance Motion of ROVs Based on a Reference Model

Fernandes¹,

Sørensen²,

Donha³

2015

MIC

Self Cite

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“…Hence, having accurate models for prediction and control is desirable; however, this is not a simple task due to the highly nonlinear behavior that appears with the fluid-vehicle interaction [3]. The navigation, guidance, and control (NGC) system for an underwater vehicle can have different degrees of sophistication, depending on the type of operation that is to be performed and the autonomy levels that need to be achieved [1,2,4,5].…”

Section: Introductionmentioning

confidence: 99%

Development of a Low-Level Control System for the ROV Visor3

Rúa

Vásquez

2016

International Journal of Navigation and Observation

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This paper addresses the development of the simulation of the low-level control system for the underwater remotely operated vehicle Visor3. The 6-DOF mathematical model of Visor3 is presented using two coordinated systems: Earth-fixed and body-fixed frames. The navigation, guidance, and control (NGC) structure is divided into three layers: the high level or the mission planner; the mid-level or the path planner; and the low level formed by the navigation and control systems. The nonlinear model-based observer is developed using the extended Kalman filter (EKF) which uses the linearization of the model to estimate the current state. The behavior of the observer is verified through simulations using Simulink®. An experiment was conducted with a trajectory that describes changes in the x and y and yaw components. To accomplish this task, two algorithms are compared: a multiloop PID and PID with gravity compensation. These controllers and the nonlinear observer are tested using the 6-DOF mathematical model of Visor3. The control and navigation systems are a fundamental part of the low-level control system that will allow Visor3’s operators to take advantage of more advanced vehicle’s capabilities during inspection tasks of port facilities, hydroelectric dams, and oceanographic research.

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“…Paper [11] develops a ROV automated control system based on multidimensional PID regulator whose operation is corrected by reference model, and an observer with a high coefficient of amplification. Article [12] synthesizes, to manage ROV, an adaptive neural network regulator based on the observer.…”

Section: Literature Review and Problem Statementmentioning

confidence: 99%

“…3, the following designations are adopted: -ЕМ R,V,m -reference submodels of SAC in accordance with (9), (11) and (17); -ІМ R,V,T,P, p, m -inverse models of ROV elements in accordance with (10), (12), (13), (15), (16) and (18); -CU T,M(i) -compensation units of indeterminate forces and moments of ROV and propulsion devices, respectively;…”

Section: { }mentioning

confidence: 99%