Robust-Guaranteed Approximation of Disturbance Invariant Set for Systems with Near-Unit-Disk Spectral Radius

  • Duc Giap Nguyen; 
  • Park, Suyong; 
  • Li, Nan; 
  • Park, Jinrak; 
  • Kim, Dohee; 
  • 외 2명
Citations

WEB OF SCIENCE

1
Citations

SCOPUS

1

초록

This study presents a practical algorithm for approximating the Robust Positively Invariant (RPI) set within the context of robust Tube Model Predictive Control (MPC) for discrete-time, linear time-invariant systems. When the stable matrix exhibits a spectral radius close to the unit disk, computing the RPI set becomes challenging, potentially rendering it infeasible. We first analyze the impact of the spectral radius on RPI set convergence, providing an insight into the problem. Subsequently, we propose an approach to integrate approximation into the RPI set computation while preserving the robustness of the corresponding tightened sets. This is achieved by enforcing the upper and lower dimensional bounds of the RPI set during computation. Additionally, we incorporate disturbance estimation error bounding into the Tube MPC framework to address substantial additive disturbances. These disturbances, if directly treated by Tube MPC, otherwise lead to over-conservative or empty tightened state and control sets. Throughout the study, we demonstrate the effectiveness of the proposed algorithm through numerical simulations of a car-following problem.

키워드

MODEL-PREDICTIVE CONTROL; OBSERVER
제목
Robust-Guaranteed Approximation of Disturbance Invariant Set for Systems with Near-Unit-Disk Spectral Radius
저자
Duc Giap Nguyen; Park, Suyong; Li, Nan; Park, Jinrak; Kim, Dohee; Eo, Jeong Soo; Han, Kyoungseok
DOI
10.1109/CDC56724.2024.10886661
발행일
2024
유형
Proceedings Paper
저널명
2024 IEEE 63RD CONFERENCE ON DECISION AND CONTROL, CDC
페이지
1801 ~ 1806