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ACTA MECHANICA ET IMPERIUM

Publishing model: Online

ISSN: 2400-9900

ABOUT JOURNAL

Acta Mechanica et Imperium is an electronic journal published 4 times per year.

This edition is focused on the publication of topical materials related to mechanics and control, also covering a wide range of subject areas related to modern research and development in these fields.

In addition to regular issues, the journal publishes select special issues on topics of current interest, such as: microgravity, space station technology, geostationary orbits, and space economics. Other subject areas include Guidance Navigation & Control, Attitude & Orbital Dynamics, Mission Design, Operation & Optimization, Space Power & Propulsion, Advanced Space Materials, Sensors, Actuators & On-Board Equipment, Space Projects & Lessons Learned, Space Structures On The Moon & Mars, Lunar & Asteroid Resources, Remote Sensing Applications, Artificial Intelligence In Space Applications.

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Editor-in-Chief

Yury N. Razoumny

Professor Doctor, Director of Academy of Engineering of RUDN University, Academician of Russian Academy of Cosmonautics, Academician of International Academy of Astronautics, IAA, Lifetime Associate Fellow, American Institute of Aeronautics and Astronautics, AIAA

Latest Articles

Optimal robust online tracking control for space manipulator in task space using off-policy reinforcement learning

Hongji Zhuang, Hang Zhou, Qiang Shen, Shufan Wu, Vladimir Yu. Razoumny, Yury N. Razoumny

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Optimal robust online tracking control for space manipulator in task space using off-policy reinforcement learning

Hongji Zhuang, Hang Zhou, Qiang Shen, Shufan Wu, Vladimir Yu. Razoumny, Yury N. Razoumny

View PDF
Optimal robust online tracking control for space manipulator in task space using off-policy reinforcement learning

Hongji Zhuang, Hang Zhou, Qiang Shen, Shufan Wu, Vladimir Yu. Razoumny, Yury N. Razoumny

View PDF
Optimal robust online tracking control for space manipulator in task space using off-policy reinforcement learning

Hongji Zhuang, Hang Zhou, Qiang Shen, Shufan Wu, Vladimir Yu. Razoumny, Yury N. Razoumny

View PDF
Optimal robust online tracking control for space manipulator in task space using off-policy reinforcement learning

Hongji Zhuang, Hang Zhou, Qiang Shen, Shufan Wu, Vladimir Yu. Razoumny, Yury N. Razoumny

View PDF