Dynamics Simulation of Grasping Process of Underwater Vehicle-Manipulator System

Chang, Zongyu; Yang, Ziqiang; Zheng, Zhongqiang; Zhao, Lin; Shen, Kunfan

doi:10.3390/jmse9101131

Cited by 7 publications

(5 citation statements)

References 83 publications

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“…Figure 9 shows the module for calculating the desired generalized coordinates based on the method proposed in [29] using Equation (13).…”

Section: Resultsmentioning

confidence: 99%

“…The outputs of the block are position and vector q. Figure 9 shows the module for calculating the desired generalized coordinates based on the method proposed in [29] using Equation (13). Analogous results for the second UVMS are shown in Figure 12.…”

Section: Resultsmentioning

confidence: 99%

“…However, there is an increasing interest for their use in inspection, maintenance, and repair operations that require manipulation and interaction with objects in the underwater environment. Nowadays, this is mainly performed by remotely operated vehicles (ROVs) [11] and one of the strongest research trends regards the use of Underwater Vehicle-Manipulator Systems (UVMS) [12,13]. Underwater vehicle-manipulator systems (UVMS) can fulfill underwater sampling, grabbing, operation, and other tasks in addition to observation.…”

Section: Introductionmentioning

confidence: 99%

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Cooperative Control of Underwater Vehicle–Manipulator Systems Based on the SDC Method

Kabanov

Kramar

Lipko

et al. 2022

Sensors

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The paper considers the problem of cooperative control synthesis for a complex of underwater vehicle–manipulator systems (UVMS) to perform the work of moving a cargo along a given trajectory. Here, we used the approach based on the representation of nonlinear dynamics models in the form of state space with state-dependent coefficients (SDC-form). That allowed us to apply methods of suboptimal control with feedback based on the state-dependent differential Riccati equation (SDDRE) solution at a finite time interval, providing the change in control intensity with the transient effect of the system matrices in SDC form. The paper reveals two approaches to system implementation: a general controller for the whole system and a set of independent subcontrollers for UVMSs. The results of both approaches are similar; however, for the systems with a small number of manipulators, the common structure is recommended, and for the systems with a large number of manipulators, the approach with independent subcontrollers may be more acceptable. The proposed method of cooperative control was tested on the task of cooperative control for two UVMSs with six-link manipulators Orion 7R. The simulation results are presented in the article and show the effectiveness of the proposed method.

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“…Figure 9 shows the module for calculating the desired generalized coordinates based on the method proposed in [29] using Equation (13).…”

Section: Resultsmentioning

confidence: 99%

Section: Resultsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Cooperative Control of Underwater Vehicle–Manipulator Systems Based on the SDC Method

Kabanov

Kramar

Lipko

et al. 2022

Sensors

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show abstract

“…Other works that use a decoupled approach [29][30][31], are also equivalent to the presented work because, as shown in Section 2, the corresponding equations are particular cases of the general equations of motions presented in this work.…”

Section: Discussionmentioning

confidence: 98%

A Unified Approach to Modeling and Simulation of Underwater Vehicle Multi-Manipulator Systems

León-González,

Núñez-Cruz,

Antonio-Yañez

et al. 2024

Machines

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In this article, the model of a family of underwater vehicle multi-manipulator systems (UVMMS) is obtained by considering all its elements as parts of a unique system, the model includes the forces produced on the manipulators by the movement of the vehicle, as well as the reaction forces on the vehicle produced by the movement of the manipulators. The modeling process is completed using the Newton–Euler approach through the mobile arborescent kinematic chain. This work also presents different approaches to the use of numerical implementations of the proposed model, and simulation results are included to demonstrate that the model is capable to represent the interaction between the vehicle and the manipulators. The proposed model and simulations are important because they allow the design of control strategies that consider all the elements of the system instead of neglecting the interaction forces or considering the vehicle and the arms as uncoupled elements.

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“…There have been a variety of control methods [2,3] proposed for UVMS by scholars in the field, including proportional-integral-derivative (PID) [4,5], expert system [6,7], fuzzy control theory [8], active disturbance rejection control (ADRC) [9], model predictive control (MPC) [10][11][12], neural network control [13], sliding mode control (SMC) [14,15], etc. However, many of these control theories suffer from limitations, such as ignoring disturbances, losing optimal control performance, reliance on accurate modeling, or high calculation complexity.…”

Section: Introductionmentioning

confidence: 99%

A robust optimal control by grey wolf optimizer for underwater vehicle-manipulator system

Dai,

Wang,

Shen

2023

PLoS ONE

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Underwater vehicle-manipulator system (UVMS) is a commonly used underwater operating equipment. Its control scheme has been the focus of control researchers, as it operates in the presence of lumped disturbances, including modelling uncertainties and water disturbances. To address the nonlinear control problem of the UVMS, we propose a robust optimal control approach optimized using grey wolf optimizer (GWO). In this scheme, the nonlinear dynamic model of UVMS is deduced to a linear state-space model in the case of the lumped disturbances. Then, the GWO algorithm is used to optimize the Riccati equation parameters of the H∞ controller in order to achieve the H∞ performance criterion, such as stability and disturbance rejection. The optimization is performed by evaluating the performance of the closed-loop UVMS in real-time comparison with the popular artificial intelligent algorithms, such as as ant colony algorithm (ACO), genetic algorithm (GA), and particle swarm optimization (PSO), using feedback control from the physical hardware-in-the-loop UVMS platform. This scheme can result in improved H∞ control system performance, and it is able to ensure that UVMS has strong robustness to these lumped disturbances. Last, the validity of the proposed scheme can be established, and its performance in overcoming modeling uncertainties and external disturbances can be observed and analyzed by performing the hardware-in-the-loop experiments.

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Dynamics Simulation of Grasping Process of Underwater Vehicle-Manipulator System

Cited by 7 publications

References 83 publications

Cooperative Control of Underwater Vehicle–Manipulator Systems Based on the SDC Method

Cooperative Control of Underwater Vehicle–Manipulator Systems Based on the SDC Method

A Unified Approach to Modeling and Simulation of Underwater Vehicle Multi-Manipulator Systems

A robust optimal control by grey wolf optimizer for underwater vehicle-manipulator system

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