Robust Nonlinear Path-Following Control of an AUV

Lapierre, Lionel; Jouvencel, B.

doi:10.1109/joe.2008.923554

Cited by 235 publications

(121 citation statements)

References 12 publications

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“…The Nonlinear Control Based (NCB) path following controller, has its grounds on the work done in [9], [10] on path following control for kinematic models of wheeled mobile robots and in [17], [22] on the same topic but for autonomous underwater vehicles. In contrast to the work described in [9], the usage of the virtual target principle enables the formulation of the path following problem in a non-singular manner, thus guaranteeing global convergence to the path.…”

Section: Nonlinear Based Controllermentioning

confidence: 99%

Four path following controllers for rhombic like vehicles

Silva¹,

Baglivo

Vale³

et al. 2013

2013 IEEE International Conference on Robotics and Automation

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Abstract-This paper addresses the path following problem of a wheeled mobile robot with rhombic like kinematics (two drivable and steerable wheels) operating in cluttered environments. Four path following controllers are developed to steer the kinematic model of a rhombic like vehicle (RLV) along a desired path: three are based on feedback laws derived at a kinematic level with geometrical inspiration; the fourth is a nonlinear controller built upon a kinematic model of the vehicle using Lyapunov functions. By fully exploiting the kinematic capabilities of this type of vehicles, all the developed controllers are capable of performing under two situations: when both wheels follow the same path, or when each wheel follows a different path. Simulated and experimental results are presented in the paper to illustrate the performance of the controllers. The main conclusions of these controllers are summarized, leading to a possible application in the vehicles that will operate in the remote handling missions of the International Thermonuclear Experimental Reactor (ITER).

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Section: Nonlinear Based Controllermentioning

confidence: 99%

Four path following controllers for rhombic like vehicles

Silva¹,

Baglivo

Vale³

et al. 2013

2013 IEEE International Conference on Robotics and Automation

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“…Robust controllers are well known for their immunity to disturbances, and have been widely used in underwater vehicles [5,11,16]. Robust terms were often employed to handle the approximation errors of neural networks, external disturbances, and estimation errors of adaptive controllers.…”

Section: Introductionmentioning

confidence: 99%

Fuzzy neural network-based robust adaptive control for dynamic positioning of underwater vehicles with input dead-zone

Xia¹,

Pang²,

Xue³

2015

IFS

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Abstract. This paper proposes a design for a robust adaptive controller for the Dynamical Positioning (DP) of underwater vehicles with unknown hydrodynamic coefficients, unknown disturbances and input dead-zones. First, for convenience of controller design, the Multi-Input Multi-Output (MIMO) system is divided into several Single-Input Single-Output (SISO) systems. Next, a Dynamic Recurrent Fuzzy Neural Network (DRFNN) with feedback loops is employed to approximate the unknown portion of the controller, which can greatly reduce the number of neural network inputs. A fuzzy logic dead-zone compensator is designed to cope with the unknown dead-zone characteristics of actuators. The upper bounds of the approximation errors and disturbances of the network, which are often used in existing works, are not necessary in this paper due to the presentation of a special robust compensator. Stability analysis is conducted according to the Lyapunov theorem, and the tracking error is proved to converge to zero. Simulation results indicate that the proposed controller demonstrates good performance.

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“…In consideration of disturbance caused by wave-induced hydrodynamic forces, Patompak and Nilkhamhang provided an adaptive backstepping sliding mode controller for station keeping and path following of underwater vehicle based on its dynamic model [11]. Lapierre and Jouvencel extended a kinematic controller with backstepping and Lyapunov-based techniques so as to cope with parametric uncertainties and external disturbances [12]. The controllers shown in [13][14][15] confirmed that the model-based backstepping controller outperforms the conventional linear controller for the wide range of velocities.…”

Section: Introductionmentioning

confidence: 99%

Dynamic Control and Disturbance Estimation of 3D Path Following for the Observation Class Underwater Remotely Operated Vehicle

Huang

Tang

et al. 2013

Advances in Mechanical Engineering

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This study addresses the question of 3D path following for the observation class underwater remotely operated vehicle. The dynamic model of the investigated remote operated vehicle is taken as a coupled multibody system composing of a flexible body and a rigid body. For precise control, the tether cable disturbance has been investigated as well via a dynamic model. Each element of the tethered cable even has been taken as an elastic body, and the waves and current disturbances have been taken into consideration. Based on the multibody system model, an adaptive backstepping sliding mode controller has been designed. To improve the controller's systematic robustness against disturbances, the sliding mode surface and adaptive control rule have been designed, too. Experiments have been performed in a tank, including the 3D path following controls of depth, heading, advance, sideway, polygon line, and spiral line. With current and wave disturbances having been taken into consideration, the tether effect has been analyzed, the efficacy and superiority of adaptive backstepping sliding mode control have been verified. It is further confirmed from the comparisons that the investigated method outperforms those S surface based controllers.

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Robust Nonlinear Path-Following Control of an AUV

Cited by 235 publications

References 12 publications

Four path following controllers for rhombic like vehicles

Four path following controllers for rhombic like vehicles

Fuzzy neural network-based robust adaptive control for dynamic positioning of underwater vehicles with input dead-zone

Dynamic Control and Disturbance Estimation of 3D Path Following for the Observation Class Underwater Remotely Operated Vehicle

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