Control-oriented system modeling and identification, information fusion, adaptive and learning controls, robust control, precision mechatronics, and optimization.
Additive manufacturing, agile robots, semiconductor manufacturing, nm-scale precision control, vision-based control, human-machine interaction, and vibration rejection.
National Science Foundation, Department of Energy, NASA, Department of Defense, UTC Institute of Advanced Systems Engineering, and industries.
Work from the MACS lab has been supported by the National Science Foundation, UTC Institute of Advanced Systems Engineering, Department of Energy, Department of Defense, NASA, and industries. Dr. Chen is a recipient of the National Science Foundation CAREER award and the Young Investigator Award from the ISCIE / ASME International Symposium on Flexible Automation. Members of the MACS lab have received Best Paper Award from the International Symposium on Flexible Automation, Best Vibrations Paper Award, Best Student Paper Awards on Mechatronics and Robotics from the ASME Dynamic Systems and Control Division, Best Senior Design, and best paper in session awards in various conferences.
We conduct systematic research on mass customization, short-run and high-value manufacturing, and controls of complex systems.
Control in different time scales: from precision laser-material interaction for aerospace and medical application to process reconfiguration and reclaiming materials.
Robot control and collaborative sensing for systematic fast control under slow e.g. vision feedback.
We were among the 3 teams that achieved the top results in an international benchmark on adaptive regulation.
Lab member Dan received a CoMotion Innovation Gap Award. Congratulations!
How can we create robots that consistently inspect for aerospace…
Xu Chen
Assistant Professor
Department of Mechanical Engineering
University of Washington