Investigation into the Dynamics and Control of an Underwater Vehicle-Manipulator System

Mohan, Santhakumar

doi:10.1155/2013/839046

Cited by 21 publications

(11 citation statements)

References 16 publications

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“…It must be noted here that such an aggressive movement is not employed in the first stages of treatment of injured limbs, but can be beneficial in the final stage of rehabilitation. We choose the non-smooth trajectory here to have a rectangular profile 43 1 m in width and 0.4 m in height. Furthermore, we select a cubic polynomial function in the joint space beginning at θ i0 = [0 0 0] T and ending at θ id = [2π 2π 2π] T during 7 s. Two cases will be explored here to identify the influence of uncertainties on tracking performances and on control law profiles for non-smooth trajectories.…”

Section: Taskmentioning

confidence: 99%

PSO-Lyapunov motion/force control of robot arms with model uncertainties

Mehdi

Boubaker

2014

Robotica

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SUMMARYA method for motion/force control of robot arms with model uncertainties is presented. Tracking control of complex trajectories is guaranteed using a Lyapunov approach with high-precision performance ensured using a particle swarm optimization (PSO) algorithm. Tracking performance and robustness are simulated for a robotic device for limb rehabilitation that is designed to be adapted easily to different subjects by considering model parameter uncertainties. Controller parameters are optimized offline using the PSO algorithm with Lyapunov stability conditions considered as inequality constraints. Using the control scheme, the robot can guide limbs on smooth and non-smooth trajectories, under model uncertainties and measurement noise.

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Section: Taskmentioning

confidence: 99%

PSO-Lyapunov motion/force control of robot arms with model uncertainties

Mehdi

Boubaker

2014

Robotica

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“…The control approach to decouple the system based on feedback linearization is most used by researchers. Santhakumar [17] proposed a model reference control scheme for the UVMS. Korkmaz et al [18] presented an inverse dynamics control law for an underactuated UVMS (U-UVMS).…”

Section: Introductionmentioning

confidence: 99%

Modeling and Fuzzy Decoupling Control of an Underwater Vehicle-Manipulator System

Han

Wei

et al. 2020

IEEE Access

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This paper presents the detailed modeling and simulation of the dynamic coupling between an autonomous underwater vehicle (AUV) and a manipulator. The modeling processes are described with the incorporation of the most dominating hydrodynamic effects such as added mass, lift and drag forces. The hydrodynamic coefficients are derived using strip theory and are adjusted according to dynamical similarity. A fuzzy decoupling controller (FDC) is proposed for an autonomous underwater vehicle-manipulator system (UVMS) which consists of two subsystems, an underwater vehicle and a manipulator. The proposed controller uses a fuzzy algorithm (FA) to adaptively tune the gain matrix of the error function (EF). The EF is described by the integral sliding surface function. This technique allows the off-diagonal elements developed for decoupling the system to be incorporated in the gain matrix. Tracing the FA and EF back to the principle of feedback linearization, one further obtains evidence about the decoupling and stability of the system. Moreover, a desired trajectory with the consideration of the dynamic coupling of the AUV is designed to reduce the thruster forces and manipulator's torques. This technique provides high performance in terms of tracking error norms and expended energy norms. A major contribution of this study is that it adopts the off-diagonal elements to exploit the dynamic coupling between the degrees of freedom of the subsystem and the dynamic coupling between the two subsystems. Simulation results demonstrate the effectiveness and robustness of the proposed technique in the presence of parameter uncertainties and external disturbances. INDEX TERMS AUV, dynamic coupling, decoupling control, fuzzy algorithm, hydrodynamic effect, underwater manipulator.

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“…Another special case occurs when the model has more than one body, such as in the work by the authors of [10]. Crossed effects appeared when a robot had accessories, such as a a robotic arm, on itself; in this case, the arm dynamical crossed effects must be considered [11]. If the coefficients of rotation need to be obtained, the method proposed by Lin [12] can be applied.…”

Section: Introductionmentioning

confidence: 99%

Experimental and Computational Methodology for the Determination of Hydrodynamic Coefficients Based on Free Decay Test: Application to Conception and Control of Underwater Robots

Cely

Saltarén

Portilla

et al. 2019

Sensors

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Hydrodynamic coefficients are essential for the development of underwater robots; in particular, for their design and navigation control. To obtain these coefficients, several techniques exist. These methods are usually experimental, but, more recently, some have been designed by a combination of experiments with computational methods based on Computational Fluid Dynamics (CFD). One method for obtaining the hydrodynamic coefficients of an ROV (Remote Operated Vehicle) is by using an experimental PMM (Planar Motion Mechanism) or CWC (Circular Water Channel); however, the use of these experimental infrastructures is costly. Therefore, it is of interest to obtain these coefficients in other ways, for example, by the use of simple experiments. The Free Decay Test is an ideal type of experiment, as it has a low cost and is simple to implement. In this paper, two different free decay tests were carried out, to which three different methods for obtaining coefficients were applied. They were compared with results obtained by CFD simulation to conduct a statistical analysis in order to determine their behaviours. It was possible to obtain values of the drag and added mass coefficients for the models analysed, where the values were obtained for an Underwater Drone Robot (UDrobot).

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Investigation into the Dynamics and Control of an Underwater Vehicle-Manipulator System

Cited by 21 publications

References 16 publications

PSO-Lyapunov motion/force control of robot arms with model uncertainties

PSO-Lyapunov motion/force control of robot arms with model uncertainties

Modeling and Fuzzy Decoupling Control of an Underwater Vehicle-Manipulator System

Experimental and Computational Methodology for the Determination of Hydrodynamic Coefficients Based on Free Decay Test: Application to Conception and Control of Underwater Robots

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