Dr. Hyeongjun Park

Ph.D., University of Michigan, 2014

Ph.D., University of Michigan, 2014

Lab:  Robotics, Unmanned Vehicles, and Intelligent systems CONtrol Lab (RUVICON Lab)

Research Interests

Real-time Nonlinear Model Predictive Control (MPC), Guidance and Control of Spacecraft Rendezvous and Proximity Operations, Control of Autonomous UAVs with Robotic Manipulation Capability, Hardware-in-the-Loop (HIL) Simulations, Efficient Numerical Optimization Methods and Algorithms

Recent Publications

  1. G. Cervettini, H. Park, D. Lee, S. Pastorelli, and M. Romano, “Development and Laboratory Experimentation of a Magnetorquer Control System for CubeSat using a Three-axis Simulator,” AAS/AIAA Astrodynamics Specialist Conference, Snowbird, UT, 2018.
  2. D. Lee, H. Park, M. Romano, and J. Cutler, “Development and Experimental Validation of a Multi-Algorithmic Hybrid Attitude Determination and Control System for a Small Satellite,” Aerospace Science and Technology, Vol. 78, pp. 494-509, 2018.
  3. H. Park, Q. Gong, W. Kang, C. Walton, and I. Kaminer, “Observability Analysis of an Adversarial Swarm’s Cooperation Strategy,” 14th IEEE International Conference on Control and Automation, Anchorage, AK, 2018.
  4. C. Zagaris, H. Park, J. Virgili-Llop, R. Zappulla, M. Romano, and I. Kolmanovsky, “Model Predictive Control of Spacecraft Relative Motion with Convexified Keep-Out-Zone Constraints,” Journal of Guidance, Control, and Dynamics, Vol. 41, No. 9, pp. 2054-2062, 2018.
  5. M. Mammarella, E. Capello, H. Park, G. Guglieri, and M. Romano, “Tube-Based Robust Model Predictive Control for Spacecraft Proximity Operations in the Presence of Persistent Disturbance,” Aerospace Science and Technology, Vol. 77, pp. 585-594, 2018.
  6. J. Hou, Z. Song, H. Park, H. Hofmann, and J. Sun, “Real-time Model Predictive Control for Load Fluctuations Mitigation in All-Electric Ship Propulsion Systems,” Applied Energy, Vol. 230, pp. 62-77, 2018.
  7. R. Zappulla, H. Park, J. Virgili-Llop, and M. Romano, “Real-Time Autonomous Spacecraft Rendezvous and Docking Using an Adaptive Artificial Potential Field Approach,” IEEE Transactions on Control Systems Technology, accepted.
  8. D. Lee, S. Sharma, H. Park, and J. Cutler, “Design and Optimization of a Small Satellite Communication System,” AIAA Aerospace Science Meeting, AIAA SciTech Forum, Kissimmee, FL, 2018.
  9. R. Zappulla, J. Virgili-Llop, C. Zagaris, H. Park, A. Sharp, and M. Romano, “POSEIDYN Test Bed: Experimental Evaluation of Autonomous Spacecraft Proximity Operations and Maneuvers,” AIAA Journal of Spacecraft and Rockets, Vol. 54, No. 4, pp. 825-839, 2017.
  10. J. Virgili-Llop, C. Zagaris, H. Park, R. Zappulla, and M. Romano, “Experimental Evaluation of Model Predictive Control and Inverse Dynamics Control for Spacecraft Proximity and Docking Maneuvers,” CEAS Space Journal, invited paper, 2017.
  11. H. Park, R. Zappulla, C. Zagaris, J. Virgili-Llop, and M. Romano, “Nonlinear Model Predictive Control for Spacecraft Rendezvous and Docking with a Rotating Target,” 27th AAS/AIAA Space Flight Mechanics Meeting, San Antonio, TX, 2017.
  12. D. Lee, H. Park, M. Romano, and J. Cutler, “Design and Validation of Hybrid Attitude Determination and Control System for CubeSat through Hardware-In-The-Loop Simulation,” 27th AAS/AIAA Space Flight Mechanics Meeting, San Antonio, TX, 2017.
  13. H. Park, C. Zagaris, J. Virgili-Llop, R. Zappulla, I. Kolmanovsky, and M. Romano, “Analysis and Experimentation of Model Predictive Control for Spacecraft Rendezvous and Proximity Operations with Multiple Obstacle Avoidance,” AIAA SPACE 2016, Long Beach, CA, 2016.
  14. J. Virgili-Llop, C. Zagaris, H. Park, R. Zappulla, and M. Romano, “Experimental Evaluation of Model Predictive Control and Inverse Dynamics Control for Spacecraft Proximity and Docking Maneuvers,” 6th International Conference on Astrodynamics Tools and Techniques, Darmstadt, Germany, 2016 (Best Paper Award).
  15. R. Zappulla, H. Park, J. Virgili-Llop, and M. Romano, “Experiments on Autonomous Spacecraft Rendezvous and Docking Using an Adaptive Artificial Potential Field Approach,” 26th AAS/AIAA Space Flight Mechanics Meeting, Napa, CA, 2016.
  16. H. Park, J. Sun, S. Pekarek, P. Stone, D. Opila, R. Meyer, I. Kolmanovsky, and R. DeCarlo, “Real-Time Model Predictive Control for Shipboard Power Management Using the IPA-SQP Approach,” IEEE Transactions on Control Systems Technology, Vol. 23, No. 6, pp. 2129–2143, 2015.
  17. E. Capello, H. Park, B. Tavora, G. Guglieri, and M. Romano, “Modeling and Experimental Parameter Identification of a Multicopter via a Compound Pendulum Test Rig,” 3rd IEEE Robotics & Automation Society Workshop on Research, Education, and Development of Unmanned Aerial Systems (RED-UAS), Cancun, Mexico, 2015.
  18. H. Park, R. Gupta, E. Dai, J. McCallum, G. Pietron, M. Shelton, and I. Kolmanovsky, “Quantifying Performance of a Connected Vehicle by Optimal Control,” 4th IFAC Workshop on Engine and Powertrain Control, Simulation, and Modeling (E-COSM), Columbus, OH, 2015.
  19. S. Di Cairano, H. Park, and I. Kolmanovsky, “Model Predictive Control Approach for Guidance of Spacecraft Rendezvous and Proximity Maneuvering,” International Journal of Robust and Nonlinear Control, Vol. 12, No. 4, pp. 1398–1427, 2012.