Adaptive control of free-floating manipulator in presence of stochastic input disturbances and unknown dynamical parameters

Sakha, Masoud Seyed; Kharrati, Hamed; Mehdifar, Farhad

doi:10.1177/10775463211010525

Cited by 4 publications

(2 citation statements)

References 41 publications

(56 reference statements)

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“…It is the role of the closed-loop controller to ensure the realization of the selected trajectory despite disturbances and uncertainties. Various methods can be used for such a purpose (e.g., predictive control [6] or adaptive control [36,37]). The problem of tracking of a numerically defined trajectory by the manipulator mounted on the satellite is analyzed in [38], while an approach based on input-output decoupling for a free-floating satellite with manipulator under state and input disturbances is shown in [39].…”

Section: The Obstacle Vector Field (Ovf) Methods 31 the Problem Of Co...mentioning

confidence: 99%

Bulletin of the Polish Academy of Sciences: Technical Sciences

Rybus

2022

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Manipulators mounted on small satellites will be used to perform on-orbit servicing, removal of space debris, and assembly of large orbital structures. During such operations, the manipulator must avoid collisions with the target object or the elements of the assembled structure. Planning of the manipulator trajectory is one of the major challenges for the proposed missions because the motion of the manipulator influences the position and orientation of the satellite. Thus, the dynamic equations of motion must be used during trajectory planning. Methods developed for fixed-base manipulators working on Earth cannot be directly applied. In this paper, we propose a new obstacle vector field (OVF) method for collision-free trajectory planning of a manipulator mounted on a free-floating satellite. The OVF method is based on a vector field that surrounds the obstacles and generates virtual forces that drive the manipulator around the obstacles. The OVF method is compared with the classical artificial potential field (APF) method and the rapidly exploring random trees (RRT) method. In the presented examples the trajectory planning problem is solved for a planar case in which the satellite is equipped with a 2 DoF manipulator. It is shown that the OVF method is more efficient than the APF method, i.e., it allows us to solve the trajectory planning problem in some of the cases, in which the APF method is unsuccessful. The time required to find the solution with the use of the OVF method is shorter than the time needed by the APF and the RRT method.

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Section: The Obstacle Vector Field (Ovf) Methods 31 the Problem Of Co...mentioning

confidence: 99%

Bulletin of the Polish Academy of Sciences: Technical Sciences

Rybus

2022

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“…In many cases, manipulators usually suffer from random disturbances under complex working conditions, such as electromagnetic radiation of space manipulator and sea turbulence of underwater manipulator, which seriously deteriorate the motion performance of manipulators [13]. It should be pointed out that random disturbance can't be described by a deterministic function [14], so it is essentially different from ordinary uncertain disturbance.…”

Section: Introductionmentioning

confidence: 99%

Event-triggered Stochastic Finite-time Tracking Control of Robot Manipulator with Uncertain Disturbance Neural Network Estimation

Dang,

2024

Preprint

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This study presents a novel event-triggered finite-time stochastic control method for a robot manipulator. The random moment of inertia of the manipulator system is expressed by building a stochastic dynamic model, and the parameter variation disturbance is estimated by using a stochastic configuration neural network. An event-triggered controller with uncertain disturbance rejection is proposed, which not only realizes the stochastic finite-time stability of the tracking error system, but also guarantees the safety of motion velocity, and robustly improves the tracking accuracy of the robot manipulator. Compared with the existing works, the obvious feature of the proposed method is that it can simultaneously solve the random disturbance and uncertain parameter disturbance of the manipulator system, save communication resources, and ensure that the manipulator system can reach a steady state in finite time. We also discuss the effectiveness of the proposed stochastic tracking control method. Simulation and comparative analysis results further show that the controller can be updated less frequently while guaranteeing robust tracking performance of the robot manipulator.

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Event-triggered stochastic finite-time tracking control of robot manipulator with uncertain disturbance neural network estimation

Dang,

2024

Nonlinear Dyn

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Adaptive control of free-floating manipulator in presence of stochastic input disturbances and unknown dynamical parameters

Cited by 4 publications

References 41 publications

Bulletin of the Polish Academy of Sciences: Technical Sciences

Bulletin of the Polish Academy of Sciences: Technical Sciences

Event-triggered Stochastic Finite-time Tracking Control of Robot Manipulator with Uncertain Disturbance Neural Network Estimation

Event-triggered stochastic finite-time tracking control of robot manipulator with uncertain disturbance neural network estimation

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