Robust tube-based model predictive control with Koopman operators
From MaRDI portal
Publication:2071959
DOI10.1016/j.automatica.2021.110114zbMath1482.93180arXiv2108.13011OpenAlexW4205769419MaRDI QIDQ2071959
Xinglong Zhang, Xin Xu, Shuyou Yu, Wei Pan, Riccardo Scattolini
Publication date: 31 January 2022
Published in: Automatica (Search for Journal in Brave)
Full work available at URL: https://arxiv.org/abs/2108.13011
Sensitivity (robustness) (93B35) Nonlinear systems in control theory (93C10) Operator-theoretic methods (93B28) Model predictive control (93B45)
Related Items
On the solution of Caputo fractional high-order three-point boundary value problem with applications to optimal control ⋮ Sampling‐based 3‐D line‐of‐sight PWA model predictive control for autonomous rendezvous and docking with a tumbling target ⋮ Adaptive data-driven fault-tolerant control for nonlinear systems: Koopman-based virtual actuator approach ⋮ A hierarchical control scheme for multiple aerial vehicle transportation systems with uncertainties and state/input constraints
Uses Software
Cites Work
- A data-driven approximation of the koopman operator: extending dynamic mode decomposition
- On the inverse function theorem
- A hierarchical multi-rate MPC scheme for interconnected systems
- On convergence of extended dynamic mode decomposition to the Koopman operator
- Robust model predictive control of constrained linear systems with bounded disturbances
- Linear predictors for nonlinear dynamical systems: Koopman operator meets model predictive control
- Constrained model predictive control: Stability and optimality
- Robust multi-rate predictive control using multi-step prediction models learned from data
- Data-driven approximation of the Koopman generator: model reduction, system identification, and control
- Koopman operator-based model reduction for switched-system control of PDEs
- Tube-based robust nonlinear model predictive control
- The Local Stabilizability Problem for Nonlinear Systems
- Generalized Gradients and Applications
- Generalizing Koopman Theory to Allow for Inputs and Control
- Learning Model Predictive Control for Iterative Tasks. A Data-Driven Control Framework
- Data-Driven Model Predictive Control using Interpolated Koopman Generators
- Adaptive Stochastic MPC Under Time-Varying Uncertainty
- Min-max control of constrained uncertain discrete-time linear systems
- Unnamed Item
- Unnamed Item