MiResolved Acceleration Control for Underwater Vehicle-Manipulator Systems: Continuous and Discrete Time Approach

Sagara, Shinichi

doi:10.5772/6715

Cited by 3 publications

(5 citation statements)

References 12 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…1. the controller receives the reference, r(k), at the time instant t = kT s ; 2. based on the dynamic model of the system and on the current states, x(k), and disturbances, w(k), an optimization process is performed over the prediction horizon, p, to minimize the cost function given in equation (32). The optimization is done through the calculation of an optimum control sequence, û, over the control horizon, c; 3. the first element of the control sequence is associated with the control input u(k), and sent to the system; 4. this process is repeated until k = N.…”

Section: Control Algorithmsmentioning

confidence: 99%

“…41 The A-MPC has advantages once it is discrete, builtin using an optimal control law, imposing actuators constraints, while compensating for parameters uncertainties and wave-induced disturbances. Moreover, the computational load of the A-MPC is reduced in comparison with the NMPC adopted by other works, since in the A-MPC the optimization performed at each time step is convex and the number of decisions variables is reduced to control inputs, as shown on equation (32). Also, ROVs have slow dynamics compared to cruising type AUVs, for example, which turns the adopted strategy ideal for this problem, since sampling rate restrictions limit the MPC application to slow dynamic systems.…”

Section: Control Algorithmsmentioning

confidence: 99%

“…31 Therefore, in this work a realistic representation of the thruster dynamics is made with the lookup table approach, as in Sagara. 32 To construct the lookup table, the generated thrust was measured by a Bollard Pull experiment in forward and reverse modes for all the admissible range of the commanded signal. Then, the curve shown in Figure 3 is raised, representing the thrust gain, K , as a function of the input (commanded signal), a .…”

Section: Mathematical Modelmentioning

confidence: 99%

See 2 more Smart Citations

Station-keeping of a ROV under wave disturbance: Modeling and control design

Oliveira

Donha

Fleury

et al. 2022

Proceedings of the Institution of Mechanical Engineers, Part M:

View full text Add to dashboard Cite

Remotely Operated Vehicles (ROVs) working close to the sea surface are subjected to wave disturbances that affect their positioning. To treat this problem, we present a control scheme for the dynamic positioning of ROVs under wave disturbances and at low operation depths. The approach is composed of an Augmented Wave Filter (AWF) based on the Extended Kalman Filter (EKF) algorithm and an Adaptive-Model Predictive Control (A-MPC). The filter provides the optimal motion states and wave height estimation to the A-MPC, which calculates the control efforts based on the receding horizon approach. The scheme is tested through numerical simulations on the depth control of the Mandi II-ROV at the diving plane. The results are compared to those of a standard Proportional-Integral-Derivative (PID) controller. To perform realistic simulations, a detailed mathematical model is presented, considering the rigid body-motion, hydrodynamic and hydrostatic forces, thrusters dynamics, and onboard sensor measurements. The simulations are performed for different scenarios, considering the dynamic positioning in still waters and the station-keeping under wave disturbances for significant heights of 1 and 2 m. The controller robustness to parameter variation is assessed by using Monte-Carlo simulation. Results have shown improved performance for the A-MPC in terms of positioning errors, motion oscillations, and drift attenuation in comparison to a PID controller. The Monte-Carlo simulation reveals enhanced robustness to the A-MPC, which is associated with the greater variance for the control forces. Also, the filter performed very well in all the tests, producing an accurate estimate of the wave-induced height and providing an off-set free control.

show abstract

Section: Control Algorithmsmentioning

confidence: 99%

Section: Control Algorithmsmentioning

confidence: 99%

Section: Mathematical Modelmentioning

confidence: 99%

See 1 more Smart Citation

Station-keeping of a ROV under wave disturbance: Modeling and control design

Oliveira

Donha

Fleury

et al. 2022

Proceedings of the Institution of Mechanical Engineers, Part M:

View full text Add to dashboard Cite

show abstract

“…presented a continuous and a discrete version of the resolved acceleration control method for UVMSs. Unlike conventional approaches, this method obtains the desired values for the joints from kinematic and momentum equations with feedback of task-space signals Sagara (2009). also presented two types of disturbance observers for the UUV, to improve the compensation provided by the resolved acceleration control method for the variation of hydrodynamic parameters and disturbances induced by the manipulator motion.…”

mentioning

confidence: 99%

“…The I-AUV model is based on the Twin-Burger AUV equipped with a 2-DoFs manipulator with cylindrical-shaped links of stainless steel. This case of study is inspired by the works ofSagara (SAGARA et al, 2001;ISHITSUKA;ISHII, 2004;YATOH;TAMURA, 2008;SAGARA, 2009;TAIRA;OYA, 2018;TAIRA; OYA, 2020;AMBAR, 2020), who studied the motion control of I-AUVs using the Twin-Burger in some of them.…”

mentioning

confidence: 99%

Estratégias modulares aplicadas ao controle de sistemas do tipo veículo-manipulador subaquático durante o transporte cooperativo.

Oliveira

View full text Add to dashboard Cite

The demand for natural resources (e.g., oil and gas, minerals, etc.), together with the high cost and operators fatigue associated with the classical teleoperation approach used by the offshore industry in Remotely Operated Vehicles (ROVs), brings the need for a higher degree of automation in the intervention tasks. To meet this requirement, the Underwater Vehicle-Manipulator Systems (UVMSs) are intended to be used in an autonomous way to perform Inspection, Maintenance and Repair (IMR) operations in the next fell years. Also, there is an increasing demand for alternative means of transportation in the underwater environment to assist in construction, deep-sea mining and general dexterous manipulation, which a single UVMS cannot perform. This work focuses on the motion control and coordination of UVMSs during cooperative transportation. Among the theoretical developments, the main contribution is the introduction of the Modular Control Methodology (MCM) for general multibody systems, whose potential engineering applications go beyond the class of problems that originally motivated this thesis. This novel methodology simplifies the control synthesis with a hierarchical approach, using standard controllers for the subsystems in the lowest levels of the control hierarchy and enforcing the constraints a posteriori. It also enables control allocation in the case of overactuation and optimal control synthesis. The MCM can also be used for coordination during cooperative transportation, since the prescribed formation can be treated as a set of constraints among the agents according to the established communication topology. The contributions made here are tested through numerical simulations in different scenarios.

show abstract