Collision prediction and avoidance for satellite ultra-close relative motion with zonotope-based reachable sets

Xu, Zhanpeng; Chen, Xiaoqian; Huang, Yiyong; Bai, Yuzhu; Chen, Qifeng

doi:10.1177/0954410018810255

Cited by 9 publications

(3 citation statements)

References 41 publications

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“…Stursberg et al used a counterexample-guided verification approach to prove the correctness of a cruise control system, which is modelled as a hybrid automaton [39]. Xu et al proposed a collision prediction approach for satellites with zonotope-based reachable sets, in which the satellites are simplified as cuboids to compute reachable domains and dangerous domains with uncertain motions [40]. These works focus on proving the correctness of a system.…”

Section: B Predictions Of Train Operationsmentioning

confidence: 99%

A Relative Operation-Based Separation Model for Safe Distances of Virtually Coupled Trains

Chai

Wang

Tang

et al. 2024

IEEE Trans. Intell. Veh.

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Virtual coupling is a novel railway transport concept that allows trains to split and join on-the-fly by switching from mechanical to virtual couplers. One of the main challenges in applying virtual coupling in metro railways is to reduce the tracking distance between trains without compromising safety. This paper proposes a relative operation-based train separation model to reduce the safe distance between trains. This model applies a fault tolerance principle. The principle is that the preceding train normally operates for a time interval from its last-known state before initiating an emergency brake to stop the train. A difficulty in applying the proposed model is to predict the boundary of all possible time-position trajectories of the preceding train, which is the reachability problem of a hybrid system. To solve this problem, we formalise the operation of the preceding train by a parameterized hybrid automaton. A polytope-based algorithm is then developed for computing an over-approximated reachable set of the automaton. We compare our approach with a state-of-the-art relative braking distance-based train separation model for virtual coupling on a concrete metro line in Chengdu, China, and evaluate the method with several benchmarks. The results demonstrate that the relative operation-based model substantially reduces the safe distances between trains. Compared to conventional approaches, the proposed model provides a considerable 90.7% decrease in unnecessary waiting time at railway stations for virtually coupled trains and a 4.9% increase in the capacity of the given railway lines.

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Section: B Predictions Of Train Operationsmentioning

confidence: 99%

A Relative Operation-Based Separation Model for Safe Distances of Virtually Coupled Trains

Chai

Wang

Tang

et al. 2024

IEEE Trans. Intell. Veh.

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“…In this section the idea of Reachable Sets (RS) and their analysis (Reachability Analysis, RA) is introduced, as well as their relationship with control and estimation of systems. The technique has been used, for instance, in the context of rendezvous of spacecraft (Sanchez et al, 2019), and has many applications in the area of safety for trajectories of vehicles (Xu et al, 2019). This background material constitutes the foundational framework for Section 5.…”

Section: Reachability Analysismentioning

confidence: 99%

Manoeuvre detection in Low Earth Orbit with Radar Data

Montilla¹,

Sanchez²,

Vázquez³

et al. 2022

Preprint

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This work outlines and assesses several methods for the detection of manoeuvres in Low Earth Orbit (LEO) from surveillance radar data. To be able to detect manoeuvres, the main starting assumption is that the object under analysis has an orbit known with a sufficient degree of precision. Based on the precise (a posteriori) orbit and radar data, several manoeuvre detection methods are presented; one is based on unscented Kalman filtering, whereas two others algorithms are based on reachability analysis of the state, which correlates its prediction set with the next track from the radar. The filtering algorithm can be extended for several radar tracks, whereas the reachability-based methods are more precise in detecting manoeuvres. Then, to inherit the best properties of both classes of algorithms, a manoeuvre detection filter that combines both concepts is finally presented. Manoeuvre detection results are presented first for simulated scenarios-for validation and calibration purposes-and later for real data. Radar information comes from the Spanish Space Surveillance Radar (S3TSR), with real manoeuvre information and high-quality ephemerides. The results show promise, taking into account that a single surveillance radar is the only source of data, obtaining manoeuvre detection rates of more than 50% and false positive rates of less than 10%.

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“…(Hartley, 2015) provides a tutorial and a detailed discussion. Among the many different approaches that have been developed to explicitly address robustness, we may count feedback corrections (Baldwin et al, 2013), the extended command governor (Petersen et al, 2014), worst-case analysis (Louembet et al, 2015;Xu et al, 2018), stochastic trajectory optimization (Jewison and Miller, 2018), chance constrained MPC (Gavilan et al, 2012;Zhu et al, 2018), sampling-based MPC (Mammarella et al, 2020), tube-based MPC (Mammarella et al, 2018;Dong et al, 2020), and reactive collision avoidance (Scharf et al, 2006). In addition to various uncertainties, anomalous system behavior such as guidance system shutdowns, thruster failures, and loss of sensing, also poses unique challenges in RPO.…”

Section: Rendezvous and Proximity Operationsmentioning

confidence: 99%

Advances in Trajectory Optimization for Space Vehicle Control

Malyuta¹,

Yu²,

Elango³

et al. 2021

Preprint

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Space mission design places a premium on cost and operational efficiency. The search for new science and life beyond Earth calls for spacecraft that can deliver scientific payloads to geologically rich yet hazardous landing sites. At the same time, the last four decades of optimization research have put a suite of powerful optimization tools at the fingertips of the controls engineer. As we enter the new decade, optimization theory, algorithms, and software tooling have reached a critical mass to start seeing serious application in space vehicle guidance and control systems. This survey paper provides a detailed overview of recent advances, successes, and promising directions for optimization-based space vehicle control. The considered applications include planetary landing, rendezvous and proximity operations, small body landing, constrained attitude reorientation, endo-atmospheric flight including ascent and reentry, and orbit transfer and injection. The primary focus is on the last ten years of progress, which have seen a veritable rise in the number of applications using three core technologies: lossless convexification, sequential convex programming, and model predictive control. The reader will come away with a well-rounded understanding of the state-of-the-art in each space vehicle control application, and will be well positioned to tackle important current open problems using convex optimization as a core technology.

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Collision prediction and avoidance for satellite ultra-close relative motion with zonotope-based reachable sets

Cited by 9 publications

References 41 publications

A Relative Operation-Based Separation Model for Safe Distances of Virtually Coupled Trains

A Relative Operation-Based Separation Model for Safe Distances of Virtually Coupled Trains

Manoeuvre detection in Low Earth Orbit with Radar Data

Advances in Trajectory Optimization for Space Vehicle Control

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