946 research outputs found
Dynamics and Control of Spacecraft Rendezvous By Nonlinear Model Predictive Control
This doctoral research investigates the fundamental problems in the dynamics and control of spacecraft rendezvous with a non-cooperative tumbling target. New control schemes based on nonlinear model predictive control method have been developed and validated experimentally by ground-based air-bearing satellite simulators. It is focused on the autonomous rendezvous for a chaser spacecraft to approach the target in the final rendezvous stage. Two challenges have been identified and investigated in this stage: the mathematical modeling of the targets tumbling motion and the constrained control scheme that is solvable in an on-line manner. First, the mathematical description of the tumbling motion of the target spacecraft is proposed for the chaser spacecraft to rendezvous with the target. In the meantime, the practical constraints are formulated to ensure the safety and avoid collision during the final approaching stage. This set of constraints are integrated into the trajectory planning problem as a constrained optimization problem. Second, the nonlinear model predictive control is proposed to generate the feedback control commands by iteratively solving an open-loop discrete-time nonlinear optimal control problem at each sampling instant. The proposed control scheme is validated both theoretically and experimentally by a custom-built spacecraft simulator floating on a high-accuracy granite table. Computer software for electronic hardware for the spacecraft simulator and for the controller is designed and developed in house. The experimental results demonstrate the effectiveness and advantages of the proposed nonlinear model predictive control scheme in a hardware-in-the-loop environment. Furthermore, a preliminary outlook is given for future extension of the spacecraft simulator with consideration of the robotic arms
Autonomous Robots for Active Removal of Orbital Debris
This paper presents a vision guidance and control method for autonomous
robotic capture and stabilization of orbital objects in a time-critical manner.
The method takes into account various operational and physical constraints,
including ensuring a smooth capture, handling line-of-sight (LOS) obstructions
of the target, and staying within the acceleration, force, and torque limits of
the robot. Our approach involves the development of an optimal control
framework for an eye-to-hand visual servoing method, which integrates two
sequential sub-maneuvers: a pre-capturing maneuver and a post-capturing
maneuver, aimed at achieving the shortest possible capture time. Integrating
both control strategies enables a seamless transition between them, allowing
for real-time switching to the appropriate control system. Moreover, both
controllers are adaptively tuned through vision feedback to account for the
unknown dynamics of the target. The integrated estimation and control
architecture also facilitates fault detection and recovery of the visual
feedback in situations where the feedback is temporarily obstructed. The
experimental results demonstrate the successful execution of pre- and
post-capturing operations on a tumbling and drifting target, despite multiple
operational constraints
Robotic Manipulation and Capture in Space: A Survey
Space exploration and exploitation depend on the development of on-orbit robotic capabilities for tasks such as servicing of satellites, removing of orbital debris, or construction and maintenance of orbital assets. Manipulation and capture of objects on-orbit are key enablers for these capabilities. This survey addresses fundamental aspects of manipulation and capture, such as the dynamics of space manipulator systems (SMS), i.e., satellites equipped with manipulators, the contact dynamics between manipulator grippers/payloads and targets, and the methods for identifying
properties of SMSs and their targets. Also, it presents recent work of sensing pose and system states, of motion planning for capturing a target, and of feedback control methods for SMS during motion or interaction tasks. Finally, the paper reviews major ground testing testbeds for capture operations, and several notable missions and technologies developed for capture of targets on-orbit
Attitude Takeover Control for Noncooperative Space Targets Based on Gaussian Processes with Online Model Learning
One major challenge for autonomous attitude takeover control for on-orbit
servicing of spacecraft is that an accurate dynamic motion model of the
combined vehicles is highly nonlinear, complex and often costly to identify
online, which makes traditional model-based control impractical for this task.
To address this issue, a recursive online sparse Gaussian Process (GP)-based
learning strategy for attitude takeover control of noncooperative targets with
maneuverability is proposed, where the unknown dynamics are online compensated
based on the learnt GP model in a semi-feedforward manner. The method enables
the continuous use of on-orbit data to successively improve the learnt model
during online operation and has reduced computational load compared to standard
GP regression. Next to the GP-based feedforward, a feedback controller is
proposed that varies its gains based on the predicted model confidence,
ensuring robustness of the overall scheme. Moreover, rigorous theoretical
proofs of Lyapunov stability and boundedness guarantees of the proposed
method-driven closed-loop system are provided in the probabilistic sense. A
simulation study based on a high-fidelity simulator is used to show the
effectiveness of the proposed strategy and demonstrate its high performance.Comment: 17 pages, 14 figures. Submitted to in IEEE Transactions on Aerospace
and Electronic System
Adaptive Estimation and Heuristic Optimization of Nonlinear Spacecraft Attitude Dynamics
For spacecraft conducting on-orbit operations, changes to the structure of the spacecraft are not uncommon. These planned or unanticipated changes in inertia properties couple with the spacecraft\u27s attitude dynamics and typically require estimation. For systems with time-varying inertia parameters, multiple model adaptive estimation (MMAE) routines can be utilized for parameter and state estimates. MMAE algorithms involve constructing a bank of recursive estimators, each assuming a different hypothesis for the systems dynamics. This research has three distinct, but related, contributions to satellite attitude dynamics and estimation. In the first part of this research, MMAE routines employing parallel banks of unscented attitude filters are applied to analytical models of spacecraft with time-varying mass moments of inertia (MOI), with the objective of estimating the MOI and classifying the spacecraft\u27s behavior. New adaptive estimation techniques were either modified or developed that can detect discontinuities in MOI up to 98 of the time in the specific problem scenario.Second, heuristic optimization techniques and numerical methods are applied to Wahba\u27s single-frame attitude estimation problem,decreasing computation time by an average of nearly 67 . Finally, this research poses MOI estimation as an ODE parameter identification problem, achieving successful numerical estimates through shooting methods and exploiting the polhodes of rigid body motion with results, on average, to be within 1 to 5 of the true MOI values
Suboptimal LQR-based spacecraft full motion control: Theory and experimentation
Abstract This work introduces a real time suboptimal control algorithm for six-degree-of-freedom spacecraft maneuvering based on a State-Dependent-Algebraic-Riccati-Equation (SDARE) approach and real-time linearization of the equations of motion. The control strategy is sub-optimal since the gains of the linear quadratic regulator (LQR) are re-computed at each sample time. The cost function of the proposed controller has been compared with the one obtained via a general purpose optimal control software, showing, on average, an increase in control effort of approximately 15%, compensated by real-time implementability. Lastly, the paper presents experimental tests on a hardware-in-the-loop six-degree-of-freedom spacecraft simulator, designed for testing new guidance, navigation, and control algorithms for nano-satellites in a one-g laboratory environment. The tests show the real-time feasibility of the proposed approach
Autonomous Rendezvous with a non-cooperative satellite: trajectory planning and control
Con la nascita di nuove problematiche e nuove esigenze in ambito spaziale, le più importanti riguardanti il tema della mitigazione dei detriti spaziali o dell’assistenza e del servizio dei satelliti in orbita, lo scenario di rendez-vous autonomo tra un satellite inseguitore e un satellite target non cooperativo sta diventando sempre più centrale, ambizioso e accattivante.
Il grande scoglio da superare, tuttavia, consiste nell’individuazione di una strategia di approccio robusta e vincente: mentre l’esecuzione di una manovra di rendez-vous e docking o cattura con satellite cooperativo è già stata collaudata e possiede una consolidata eredità di volo, il rendez-vous autonomo con satellite non cooperativo ed in stato di tombolamento è uno scenario agli albori, con pochi studi al riguardo. Lo scopo di questa tesi consiste nell’identificazione di una strategia di approccio che consideri le principali problematiche legate al tema in questione, ovvero la non-cooperazione e le scarse informazioni sullo stato di moto del target da raggiungere.
Queste due complicazioni portano alla necessità di eseguire un moto di ispezione del satellite target e alla considerazione di numerosi vincoli nella progettazione della traiettoria di ispezione e di approccio. Un controllore adatto a trattare questo problema
complesso e multi-vincolato è il Model Predictive Controller, in forma lineare o non lineare, abbinato ad un filtro di Kalman. La capacità di questo controllore di previsione e pianificazione di una traiettoria d’approccio, a partire da stime di posizione relativa
tra target e inseguitore, permette di portare a termine la manovra in modo sicuro e robusto.According to the rise of new problems and new demands in the space field, the most important concerning the mitigation of space debris or the spacecraft on-orbit servicing and assistance themes, the Autonomous Rendezvous scenario between a chase satellite
and a non-cooperative target satellite is becoming increasingly significant, ambitious, and attractive.
The main issue to overcome, however, consists in the identification of a robust and successful approach strategy: while the execution of a rendezvous and docking or capture maneuver with a cooperative satellite has already been tested and
holds a solid flight heritage, the autonomous rendezvous with a non-cooperative satellite in a state of tumbling motion is a scenario in the early days, with few studies about it and a not yet mature technology. The aim of this thesis consists in the identification
of an approach strategy that deals with the main challenges related to the considered problem, namely non-cooperativeness and exiguous information about the target to be reached. These two issues lead to the need of performing an inspection motion and
considering several constraints in the trajectory design. A controller suitable to handle this complex and multi-constrained problem is the Model Predictive Controller, in a linear or non-linear form, paired with a Kalman filter. The ability of this controller to predict and plan an approaching trajectory, starting from estimates of the relative position between the target and the chaser, allows to complete the approaching maneuver safely and in a robust way
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