Dynamic Tube MPC for Nonlinear Systems
Name
1907.06553.pdf
Description
Accepted version
Size
2.44 MB
Format
Adobe PDF
Checksum (MD5)
ac062728eb822ff09beb167da0171bf5
Author(s)
Lopez, Brett Thomas
Slotine, Jean-Jacques E
How, Jonathan P
Date Issued
August 2019
Journal
2019 American Control Conference
Publisher
Institute of Electrical and Electronics Engineers (IEEE)
Citation
Lopez, Brett T. et al. "Dynamic Tube MPC for Nonlinear Systems." 2019 American Control Conference, July 2019, Philadelphia, Pennsylvania, Institute of Electrical and Electronics Engineers, August 2019. © 2019 American Automatic Control Council
Version
Author's final manuscript
Abstract
Modeling error or external disturbances can severely degrade the performance of Model Predictive Control (MPC) in real-world scenarios. Robust MPC (RMPC) addresses this limitation by optimizing over feedback policies but at the expense of increased computational complexity. Tube MPC is an approximate solution strategy in which a robust controller, designed offline, keeps the system in an invariant tube around a desired nominal trajectory, generated online. Naturally, this decomposition is suboptimal, especially for systems with changing objectives or operating conditions. In addition, many tube MPC approaches are unable to capture state-dependent uncertainty due to the complexity of calculating invariant tubes, resulting in overly-conservative approximations. This work presents the Dynamic Tube MPC (DTMPC) framework for nonlinear systems where both the tube geometry and open-loop trajectory are optimized simultaneously. By using boundary layer sliding control, the tube geometry can be expressed as a simple relation between control parameters and uncertainty bound; enabling the tube geometry dynamics to be added to the nominal MPC optimization with minimal increase in computational complexity. In addition, DTMPC is able to leverage state-dependent uncertainty to reduce conservativeness and improve optimization feasibility. DTMPC is demonstrated to robustly perform obstacle avoidance and modify the tube geometry in response to obstacle proximity.
MIT Department
Massachusetts Institute of Technology. Aerospace Controls Laboratory
Massachusetts Institute of Technology. Nonlinear Systems Laboratory
Massachusetts Institute of Technology. Department of Aeronautics and Astronautics
Terms of Use
Creative Commons Attribution-Noncommercial-Share Alike
Persistent DSpace Link
DOI of Published Version
https://doi.org/10.23919/acc.2019.8814758
