Department of Electrical and Computer Engineering

Data-Driven Control for Robots, UAVs and Aerial Manipulators

Model-based control approaches require the mathematical model of system to be controlled, which have been widely used in many applications. However, with the increasing complexity of system dynamics, modeling process by first principles has become more difficult. When the model is inaccurate, model-based control methods would lose the utility.  As data is becoming more readily available, learning from data has then tracked more and more attentions in the control community.  In our research group, we develop a new data-driven method for nonlinear system, which will be implemented on the different robotic platforms.

  • Y. Wang, M. Leibold, J. Lee, W. Ye, J. Xie, M. Buss: Incremental Model Predictive Control for a Robot Manipulator: a Model-Free Approach. Submitted to IEEE Transactions on Control Systems Technology
Master Thesis:
  • T.H. Wang: Implementation of data-driven control for hexacopters. 2021.
Master Project:
  • D. Hallerbach and J. Kickertz: A comparison of different data driven controller design approaches. 2020.
  • H. Chang: Implementation of position system for hexacopters. (Running)
  • S. Bhatta: Incremental Model Predictive Control for Aerial Manipulators in task space. (Running)
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