Once Upon a Time Step: A Closed-Loop Approach to Robust MPC Design

成果类型:
Article
署名作者:
Parsi, Anilkumar; Bartos, Marcell; Srivastava, Amber; Gros, Sebastien; Smith, Roy S.
署名单位:
Swiss Federal Institutes of Technology Domain; ETH Zurich; Swiss Federal Institutes of Technology Domain; ETH Zurich; Indian Institute of Technology System (IIT System); Indian Institute of Technology (IIT) - Delhi; Norwegian University of Science & Technology (NTNU)
刊物名称:
IEEE TRANSACTIONS ON AUTOMATIC CONTROL
ISSN/ISSBN:
0018-9286
DOI:
10.1109/TAC.2024.3465522
发表日期:
2025
页码:
1297-1303
关键词:
Radio frequency optimization uncertainty Perturbation methods trajectory Q measurement Predictive control Constrained control predictive control for linear systems Robust control uncertain systems
摘要:
A novel robust model predictive control (MPC) algorithm is presented, whereby closed-loop constraint satisfaction is ensured using recursive feasibility of the MPC optimization. The proposed strategy considers the effects of model perturbations and disturbances occurring at only one time step. This is in contrast to existing formulations, which compute control policies that are feasible under the worst-case realizations of all model perturbations and exogenous disturbances in the MPC prediction horizon. The proposed method has an online computational complexity similar to nominal MPC methods while guaranteeing constraint satisfaction, recursive feasibility, and stability. Numerical simulations demonstrate the efficacy of our proposed approach.