Motion Simulation of an Underwater Vehicle with Mechanical Pectoral Fins Using a CFD-based Motion Simulator

Abstract-We study the software simulation of underwater physical communications, namely, underwater acoustic waves and (de)modulation of underwater acoustic digital data signals. We take into account the mobility of nodes, such as in underwater sensor networks. We also consider the integration with protocol layers above the physical layer, i.e., the link and network layers. In this context, mobility is relevant because there are underwater vehicles and environmental conditions causing displacements of sensors. Attenuation is sensitive to transmitter-receiver separation distances. Because of mobility, distances change. Our solution is based on the work of Borrowski (2010). The physical layer is modeled as Matlab functions. As a function of distance and frequency, our physical layer model takes into account attenuation and noise and their effects on a phase-shift keyed signal. We use OMNeT++ to model link and network layer protocols. The Matlab functions and OMNet++ models are linked together. While Matlab does particularly well with signal processing, OMNeT++ addresses better the protocols placed in the link layer and above.

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“…Suzuki et al have created an underwater vehicle simulator [23]. Detweiller et al have developed underwater sensor network hardware [24].…”

Section: Related Workmentioning

confidence: 99%

Simulation of underwater communications with a colored noise approximation and mobility

Barbeau

Blouin

Cervera

et al. 2015

2015 IEEE 28th Canadian Conference on Electrical and Computer Engineering (CCECE)

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“…Additionally, using an overlapping grid system, Orihara and Miyata (2003) evaluated the added resistance of ships in regular incident waves. Suzuki et al (2007) simulated the motion of an underwater vehicle with mechanical pectoral fins. To avoid the great demand of computational resources, Hu et al (2007) completed calculations of the hydrodynamic forces and moments for an autonomous underwater vehicle (AUV) in a rotating frame of reference.…”

Section: Introductionmentioning

confidence: 99%

An effective CFD approach for marine-vehicle maneuvering simulation based on the hybrid reference frames method

Wang

Huang

et al. 2015

Ocean Engineering

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a b s t r a c tThe computational efficiency of CFD on maneuverability simulation poses a great difficulty resulting in its restricted applications. A hybrid reference frames method is established that combines the rotating reference frame method and an added momentum source method. The computational domain is separated into two parts under the rotating reference frame and the inertial frame respectively. A single mesh is needed for all conditions of a testing model such as different rotating arm radius, pitch angles and drift angles. The validation is carried out based on the numerical simulations on the flow fields around the SUBOFF models including sterns and full appended models. Results show that the stability derivatives of the yawing moment and yawing force agree well with the experimental data. Using a dimensional analysis method, the influences of the rotating arm radius and linear velocity are investigated. The similarity is maintained when the radius is constant, and the rotating effect performs strongly when the radius is small. The effects of pitch angle and drift angle are also discussed when the linear velocity is fixed with the fully appended SUBOFF model.

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“…Researchers have conducted laboratory experiments and measured the forces and moments produced by oscillating fins [6,10,18,19]. Besides laboratory tests, numerical computation of unsteady hydrodynamics has been performed based on the solution of Navier-Stokes equations, and estimates of the fin forces have been obtained [20][21][22][23]. These results show that oscillating foils produce periodic forces, and their profile can be changed for the purpose of control by altering the oscillation parameters (such as bias (mean) angle, frequency, relative phase angle, rotation angle at the end of stroke, etc) of the fins.…”

Section: Introductionmentioning

confidence: 99%

“…Using this approach, the time-varying models are approximated by averaged time-invariant systems for the control law design. A fuzzy control law has been developed for the control of AUV using pectoral fins, and experimental results for swimming forward and turning have been obtained [19,23]. Neural network-based propulsion of an AUV using flexible/rigid oscillating fin has been considered [26].…”

Section: Introductionmentioning

confidence: 99%

Indirect adaptive output feedback control of a biorobotic AUV using pectoral-like mechanical fins

2009

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This paper treats the question of servoregulation of autonomous underwater vehicles (AUVs) in the yaw plane using pectoral-like mechanical fins. The fins attached to the vehicle have oscillatory swaying and yawing motion. The bias angle of the angular motion of the fin is used for the purpose of control. Of course, the design approach considered here is applicable to AUVs for other choices of oscillation patterns of the fins, which produce periodic forces and moments. It is assumed that the vehicle parameters, hydrodynamic coefficients, as well the fin forces and moments are unknown. For the trajectory control of the yaw angle, a sampled-data indirect adaptive control system using output (yaw angle) feedback is derived. The control system has a modular structure, which includes a parameter identifier and a stabilizer. For the control law derivation, an internal model of the exosignals (reference signal (constant or ramp) and constant disturbance) is included. Unlike the direct adaptive control scheme, the derived control law is applicable to minimum as well as nonminimum phase biorobotic AUVs (BAUVs). This is important, because for most of the fin locations on the vehicle, the model is a nonminimum phase. In the closed-loop system, the yaw angle trajectory tracking error converges to zero and the remaining state variables remain bounded. Simulation results are presented which show that the derived modular control system accomplishes precise set point yaw angle control and turning maneuvers in spite of the uncertainties in the system parameters using only yaw angle feedback.

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Motion Simulation of an Underwater Vehicle with Mechanical Pectoral Fins Using a CFD-based Motion Simulator

Cited by 11 publications

References 4 publications

Simulation of underwater communications with a colored noise approximation and mobility

Simulation of underwater communications with a colored noise approximation and mobility

An effective CFD approach for marine-vehicle maneuvering simulation based on the hybrid reference frames method

Indirect adaptive output feedback control of a biorobotic AUV using pectoral-like mechanical fins

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