TY - GEN
T1 - Computing Controlled Invariant Sets of Nonlinear Control-Affine Systems
AU - Brown, Scott
AU - Khajenejad, Mohammad
AU - Yong, Sze Zheng
AU - Martínez, Sonia
N1 - Publisher Copyright:
© 2023 IEEE.
PY - 2023
Y1 - 2023
N2 - In this paper, we consider the computation of controlled invariant sets (CIS) of discrete-time nonlinear control-affine systems. We propose an iterative refinement procedure based on polytopic inclusion functions, which is able to inner-approximate the maximal controlled invariant set to within a guaranteed robustness margin. In particular, this procedure allows us to guarantee the invariance of the resulting near-maximal CIS while also computing sets of control inputs which enforce the invariance. Further, we propose an alternative version of this procedure which refines the CIS by computing backward reachable sets of individual components of set unions, rather than all at once. This reduces the total number of inclusion checking operations required for convergence, especially when compared with existing methods. Finally, we compare our methods to a sampling based approach and demonstrate the improved accuracy and faster convergence.
AB - In this paper, we consider the computation of controlled invariant sets (CIS) of discrete-time nonlinear control-affine systems. We propose an iterative refinement procedure based on polytopic inclusion functions, which is able to inner-approximate the maximal controlled invariant set to within a guaranteed robustness margin. In particular, this procedure allows us to guarantee the invariance of the resulting near-maximal CIS while also computing sets of control inputs which enforce the invariance. Further, we propose an alternative version of this procedure which refines the CIS by computing backward reachable sets of individual components of set unions, rather than all at once. This reduces the total number of inclusion checking operations required for convergence, especially when compared with existing methods. Finally, we compare our methods to a sampling based approach and demonstrate the improved accuracy and faster convergence.
UR - https://www.scopus.com/pages/publications/85184830459
UR - https://www.scopus.com/pages/publications/85184830459#tab=citedBy
U2 - 10.1109/CDC49753.2023.10383613
DO - 10.1109/CDC49753.2023.10383613
M3 - Conference contribution
AN - SCOPUS:85184830459
T3 - Proceedings of the IEEE Conference on Decision and Control
SP - 7830
EP - 7836
BT - 2023 62nd IEEE Conference on Decision and Control, CDC 2023
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 62nd IEEE Conference on Decision and Control, CDC 2023
Y2 - 13 December 2023 through 15 December 2023
ER -