{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,10,11]],"date-time":"2025-10-11T03:01:14Z","timestamp":1760151674109,"version":"build-2065373602"},"reference-count":30,"publisher":"MDPI AG","issue":"5","license":[{"start":{"date-parts":[[2022,4,19]],"date-time":"2022-04-19T00:00:00Z","timestamp":1650326400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"National Key R &amp; D Program of China","award":["2017YFB0503304"],"award-info":[{"award-number":["2017YFB0503304"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Entropy"],"abstract":"<jats:p>This paper addresses the orbital rendezvous control for multiple uncertain satellites. Against the background of a pulsar-based positioning approach, a geometric trick is applied to determine the position of satellites. A discontinuous estimation algorithm using neighboring communications is proposed to estimate the target\u2019s position and velocity in the Earth\u2019s Centered Inertial Frame for achieving distributed rendezvous control. The variables generated by the dynamic estimation are viewed as virtual reference trajectories for each satellite in the group, followed by a novel saturation-like adaptive control law with the assumption that the masses of satellites are unknown and time-varying. The rendezvous errors are proven to be convergent to zero asymptotically. Numerical simulations considering the measurement fluctuations validate the effectiveness of the proposed control law.<\/jats:p>","DOI":"10.3390\/e24050575","type":"journal-article","created":{"date-parts":[[2022,4,19]],"date-time":"2022-04-19T22:07:26Z","timestamp":1650406046000},"page":"575","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":1,"title":["Adaptive Orbital Rendezvous Control of Multiple Satellites Based on Pulsar Positioning Strategy"],"prefix":"10.3390","volume":"24","author":[{"given":"Qiang","family":"Chen","sequence":"first","affiliation":[{"name":"School of Automation Science and Electrical Engineering, Beihang University (BUAA), Beijing 100191, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Yong","family":"Zhao","sequence":"additional","affiliation":[{"name":"School of Automation Science and Electrical Engineering, Beihang University (BUAA), Beijing 100191, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Lixia","family":"Yan","sequence":"additional","affiliation":[{"name":"School of Automation Science and Electrical Engineering, Beihang University (BUAA), Beijing 100191, China"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1968","published-online":{"date-parts":[[2022,4,19]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"76","DOI":"10.1016\/j.paerosci.2018.07.007","article-title":"Spacecraft trajectory optimization: A review of models, objectives, approaches and solutions","volume":"102","author":"Shirazi","year":"2018","journal-title":"Prog. 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