Oscillatory Adaptive Yaw‐Plane Control of Biorobotic Autonomous Underwater Vehicles Using Pectoral‐Like Fins

Naik, Mugdha S.; Singh, Sahjendra N.

doi:10.1080/11762320801999746

Cited by 7 publications

(6 citation statements)

References 27 publications

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“…Geder et al (2008) developed a fuzzy logic PID controller to control the trajectory of a vehicle with two pectoral fins. Naik and Singh (2007) studied the motion control of a fish-like robot in the yaw plane. The motion of the vehicle was controlled by altering the motion of pectoral-like fins.…”

Section: Introductionmentioning

confidence: 99%

Adaptive controller for a biomimetic underwater vehicle

PlamondonNicolas

NahonMeyer

2013

J. Unmanned Veh. Sys.

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Aqua is an underwater biomimetic vehicle designed and built at McGill University that uses six oscillating paddles to produce control and propulsion forces. These oscillating paddles provide a time-periodic thrust. Using an existing dynamics model of the vehicle and a numerical simulation, an adaptive controller was developed to provide trajectory tracking capabilities to the vehicle. The performance of the controller was first assessed on a dynamics simulation using different trajectories in roll and pitch. The same controller was then tested experimentally in the Caribbean Sea. We found that the adaptive controller was able to track the roll angle with good accuracy, while the tracking error in the pitch motion was more significant.Résumé : Aqua est un véhicule sous-marin biomimétique conçu et construit à l'Université McGill. Ce véhicule utilise six nageoires oscillantes servant à le contrôler et à le propulser. À l'aide d'un modèle dynamique du véhicule et d'une simulation numérique, une commande adaptative a été élaborée afin de pouvoir suivre une trajectoire désirée du véhicule. La performance de la commande a été évaluée tout d'abord par simulation utilisant différentes trajectoires de roulis et tangage. La même commande a ensuite été testée au cours d'une séance expérimentale dans la mer des Caraïbes. Les résultats ont démontré que la commande adaptative pouvait suivre l'angle de roulis avec bonne précision alors que l'erreur de suivi dans le mouvement de tangage était plus importante. [Traduit par la Rédaction] Mots-clés : contrôles adaptatifs, biomimétique, véhicule sous-marin.

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Section: Introductionmentioning

confidence: 99%

Adaptive controller for a biomimetic underwater vehicle

PlamondonNicolas

NahonMeyer

2013

J. Unmanned Veh. Sys.

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“…Geder et al [14] developed a fuzzy logic PID controller to control the trajectory of a vehicle with two pectoral fins. Naik and Singh [15] studied the motion control of a fish-like robot in the yaw plane. The motion of the vehicle is controlled by altering the motion of pectoral-like fins.…”

Section: Introductionmentioning

confidence: 99%

A trajectory tracking controller for an underwater hexapod vehicle

Plamondon¹,

Nahon²

2009

Bioinspir. Biomim.

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This paper describes work done in the modeling and control of a low speed underwater vehicle that uses paddles instead of thrusters to move in the water. A review of previously modeled vehicles and of controller designs for underwater applications is presented. Then, a method to accurately predict the thrust produced by an oscillating flexible paddle is developed and validated. This is followed by the development of a method to determine the ideal paddle motion to produce a desired thrust. Several controllers are then developed and tested using a numerical simulation of the vehicle. We found that some model-based controllers could improve the performance of the system while others showed no benefit. Finally, we report results from experimental trials performed in an open water environment comparing the performance of the controllers. The experimental results showed that all the model-based controllers outperform the simple proportional-derivative controller. The controller giving the best performance was the model-based nonlinear controller. We also found that the vehicle was able to follow a change of a roll angle of 90 degrees in 0.7 s and to precisely follow a sinusoidal trajectory with a period of 6.28 s and an amplitude of 5 degrees.

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“…Indeed, the assumption of exact knowledge of fin forces and moments is not realistic. In recent works, adaptive control laws have been designed for BAUV models with uncertain parameters [29,30]. But the direct adaptive control design approaches of [29,30] cannot be applied to BAUV models which are nonminimum phase.…”

Section: Introductionmentioning

confidence: 99%

“…In recent works, adaptive control laws have been designed for BAUV models with uncertain parameters [29,30]. But the direct adaptive control design approaches of [29,30] cannot be applied to BAUV models which are nonminimum phase. In addition, [29] requires measurement of each state variable for feedback.…”

Section: Introductionmentioning

confidence: 99%

“…The adaptive control system has a modular structure, which includes a gradient-based identifier and a stabilizer, designed using the pole placement technique. Unlike the published work [29,30], this control system can be used for the control of minimum as well as nonminimum phase BAUVs. This is of practical importance, since the vehicle model is nonminimum phase for the choice of most of the locations of the fins on the vehicle and the oscillation parameters.…”

Section: Introductionmentioning

confidence: 99%

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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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Oscillatory Adaptive Yaw‐Plane Control of Biorobotic Autonomous Underwater Vehicles Using Pectoral‐Like Fins

Cited by 7 publications

References 27 publications

Adaptive controller for a biomimetic underwater vehicle

Adaptive controller for a biomimetic underwater vehicle

A trajectory tracking controller for an underwater hexapod vehicle

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

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