TY - GEN
T1 - Backup Plan Constrained Model Predictive Control
AU - Kim, Hunmin
AU - Yoon, Hyungjin
AU - Wan, Wenbin
AU - Hovakimyan, Naira
AU - Sha, Lui
AU - Voulgaris, Petros
N1 - Publisher Copyright:
© 2021 IEEE.
PY - 2021
Y1 - 2021
N2 - This article proposes a new safety concept: dynamically formulated backup plan safety. The backup plan safety is defined as the ability to complete one of the alternative missions formulated in real-time in the case of primary mission abortion. To incorporate this new safety concept in control problems, we formulate a feasibility maximization problem that adopts additional (virtual) input horizons toward the alternative missions on top of the input horizon toward the primary mission. Cost functions for the primary and alternative missions construct multiple objectives, and multi-horizon inputs evaluate them. To address the feasibility maximization problem, we develop a multi-horizon multi-objective model predictive path integral control (3M) algorithm. Model predictive path integral control (MPPI) is a sampling-based scheme that can help the proposed algorithm deal with nonlinear dynamic systems and achieve computational efficiency by parallel computation. Simulations of the aerial vehicle control problems demonstrate the new concept of backup plan safety and the performance of the proposed algorithm.
AB - This article proposes a new safety concept: dynamically formulated backup plan safety. The backup plan safety is defined as the ability to complete one of the alternative missions formulated in real-time in the case of primary mission abortion. To incorporate this new safety concept in control problems, we formulate a feasibility maximization problem that adopts additional (virtual) input horizons toward the alternative missions on top of the input horizon toward the primary mission. Cost functions for the primary and alternative missions construct multiple objectives, and multi-horizon inputs evaluate them. To address the feasibility maximization problem, we develop a multi-horizon multi-objective model predictive path integral control (3M) algorithm. Model predictive path integral control (MPPI) is a sampling-based scheme that can help the proposed algorithm deal with nonlinear dynamic systems and achieve computational efficiency by parallel computation. Simulations of the aerial vehicle control problems demonstrate the new concept of backup plan safety and the performance of the proposed algorithm.
UR - http://www.scopus.com/inward/record.url?scp=85126032813&partnerID=8YFLogxK
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U2 - 10.1109/CDC45484.2021.9683388
DO - 10.1109/CDC45484.2021.9683388
M3 - Conference contribution
AN - SCOPUS:85126032813
T3 - Proceedings of the IEEE Conference on Decision and Control
SP - 289
EP - 294
BT - 60th IEEE Conference on Decision and Control, CDC 2021
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 60th IEEE Conference on Decision and Control, CDC 2021
Y2 - 13 December 2021 through 17 December 2021
ER -