Space Robot Performance During Tangent Capture of an Uncontrolled Target Satellite

Seweryn, K.; Basmadji, Fatina Liliana; Rybus, Tomasz

doi:10.1007/s40295-022-00330-2

Cited by 5 publications

(5 citation statements)

References 34 publications

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“…Therefore, any controlling law shall be sufficiently robust to maintain its performance in the possibilities of an actuator failure or malfunction. This event is more possible in the case of direct capturing methods where capturing of objects can cause large impacts on the spacecraft (Seweryn et al, 2022). Accurate identification of system parameters is inevitable in rigid capturing missions where many parameters such as inertia, friction, geometry, and attitude must be identified to ensure the controller's performance (Aghili, 2020).…”

Section: Figurementioning

confidence: 99%

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A fault-tolerant and robust controller using model predictive path integral control for free-flying space robots

2022

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The use of manipulators in space missions has become popular, as their applications can be extended to various space missions such as on-orbit servicing, assembly, and debris removal. Due to space reachability limitations, such robots must accomplish their tasks in space autonomously and under severe operating conditions such as the occurrence of faults or uncertainties. For robots and manipulators used in space missions, this paper provides a unique, robust control technique based on Model Predictive Path Integral Control (MPPI). The proposed algorithm, named Planner-Estimator MPPI (PE-MPPI), comprises a planner and an estimator. The planner controls a system, while the estimator modifies the system parameters in the case of parameter uncertainties. The performance of the proposed controller is investigated under parameter uncertainties and system component failure in the pre-capture phase of the debris removal mission. Simulation results confirm the superior performance of PE-MPPI against vanilla MPPI.

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Section: Figurementioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

A fault-tolerant and robust controller using model predictive path integral control for free-flying space robots

2022

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“…However, designing a control system for the manipulator mounted on the satellite is dif icult due to the in luence of the manipulator's motion on the position and attitude of the servicing satellite. In close proximity to the target object, we encounter one of the following cases: the system is free-loating, the satellite is fully controlled, or the satellite control is used to give nonzero velocity before the manipulator's operations (tangent capture case) [8]. Most commonly, it is assumed that the Attitude and Orbit Control System (AOCS) for the satellite is turned off because the external forces and torques induced by satellite thrusters can cause undesirable changes of position and orientation of the end-effector, which might lead to a collision with the target object.…”

Section: Introductionmentioning

confidence: 99%

Parameter Identification of Space Manipulator's Flexible Joint

Wojtunik,

Basmadji,

Granosik

et al. 2024

JAMRIS

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It is considered to use a manipulator mounted on a satellite in order to perform active debris removal missions. Space manipulator control system needs to take the dynamic model of the satellite-manipulator system into account because of the influence of the manipulator motion on the position and attitude of the satellite. Therefore, precise modelling of the space manipulator dynamics as well as parameter identification are needed in order to improve the credibility of the simulation tools. In this paper we presented the identification of the flexible-joint space manipulator model based on dynamic equations of motion. Experiments were performed in emulated microgravity environment using planar air bearings. The arbitrarily selected joint-space trajectory was performed by the manipulator’s control system. The experiments were repeated multiple times in order to analyze the identification method sensitivity. The identification is based on Simulink SimMechanics model. Thus, the procedure can be used for any space manipulator without the need of obtaining analytical relations for dynamic equations each time. Including joint flexibility and spring viscous damping in the dynamic model allowed to reflect the experimental measurements better than the reference model could. Identified parameters of the flexible joint have values of the same magnitude as corresponding real system parameters.

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“…Thus, it is essential to implement a controlling law that is robust enough to sustain its performance in the event of actuator malfunction or failure. This circumstance is particularly probable when employing direct capture methods since the capture process can lead to significant effects on the spacecraft, as stated by Seweryn et al, 2022. However, there are major technological challenges in autonomous robotics spacecrafts. First of all, missions may involve execution of uncertain tasks in an unstructured environment.…”

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Passivity based nonlinear model predictive control (PNMPC) of multi-robot systems for space applications

Kalaycioglu

Ruiter

2023

Front. Robot. AI

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In the past 2 decades, there has been increasing interest in autonomous multi-robot systems for space use. They can assemble space structures and provide services for other space assets. The utmost significance lies in the performance, stability, and robustness of these space operations. By considering system dynamics and constraints, the Model Predictive Control (MPC) framework optimizes performance. Unlike other methods, standard MPC can offer greater robustness due to its receding horizon nature. However, current literature on MPC application to space robotics primarily focuses on linear models, which is not suitable for highly non-linear multi-robot systems. Although Nonlinear MPC (NMPC) shows promise for free-floating space manipulators, current NMPC applications are limited to unconstrained non-linear systems and do not guarantee closed-loop stability. This paper introduces a novel approach to NMPC using the concept of passivity to multi-robot systems for space applications. By utilizing a passivity-based state constraint and a terminal storage function, the proposed PNMPC scheme ensures closed-loop stability and a superior performance. Therefore, this approach offers an alternative method to the control Lyapunov function for control of non-linear multi-robot space systems and applications, as stability and passivity exhibit a close relationship. Finally, this paper demonstrates that the benefits of passivity-based concepts and NMPC can be combined into a single NMPC scheme that maintains the advantages of each, including closed-loop stability through passivity and good performance through one-line optimization in NMPC.

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Space Robot Performance During Tangent Capture of an Uncontrolled Target Satellite

Cited by 5 publications

References 34 publications

A fault-tolerant and robust controller using model predictive path integral control for free-flying space robots

A fault-tolerant and robust controller using model predictive path integral control for free-flying space robots

Parameter Identification of Space Manipulator's Flexible Joint

Passivity based nonlinear model predictive control (PNMPC) of multi-robot systems for space applications

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