TY - GEN
T1 - Multiple Scenario-based Model Predictive Control with Decision Time Limit Determination of Scenario Selection
AU - Iino, Yutaka
AU - Hayashi, Yasuhiro
N1 - Funding Information:
This work was supported by JST-Mirai Program Grant Number JPMJMI17B5, Japan.
Publisher Copyright:
© 2019 The Society of Instrument and Control Engineers - SICE.
PY - 2019/9
Y1 - 2019/9
N2 - In the Cyber Physical System or the Digital Twin, the control strategy generates multiple scenarios in the cyber world with optimization of future models and objective functions, and these scenarios are utilized to determine an optimal strategy, which is then applied to the physical world. In these procedures, the decision-making to select and fix a future scenario and its time limit are important factors. In this study, considering the scenario decision time limit, a procrastination strategy is introduced and formulated as a new model predictive control framework. It is to postpone the decision and preserve the freedom of scenario choice for the future. In the proposed method, the concept of a common admissible set for control trajectory and its branch point are introduced. A simple numerical example and an application to an energy management problem are shown to illustrate and verify the effectiveness of the proposed method.
AB - In the Cyber Physical System or the Digital Twin, the control strategy generates multiple scenarios in the cyber world with optimization of future models and objective functions, and these scenarios are utilized to determine an optimal strategy, which is then applied to the physical world. In these procedures, the decision-making to select and fix a future scenario and its time limit are important factors. In this study, considering the scenario decision time limit, a procrastination strategy is introduced and formulated as a new model predictive control framework. It is to postpone the decision and preserve the freedom of scenario choice for the future. In the proposed method, the concept of a common admissible set for control trajectory and its branch point are introduced. A simple numerical example and an application to an energy management problem are shown to illustrate and verify the effectiveness of the proposed method.
UR - http://www.scopus.com/inward/record.url?scp=85073870829&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85073870829&partnerID=8YFLogxK
U2 - 10.23919/SICE.2019.8859962
DO - 10.23919/SICE.2019.8859962
M3 - Conference contribution
AN - SCOPUS:85073870829
T3 - 2019 58th Annual Conference of the Society of Instrument and Control Engineers of Japan, SICE 2019
SP - 1486
EP - 1493
BT - 2019 58th Annual Conference of the Society of Instrument and Control Engineers of Japan, SICE 2019
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 58th Annual Conference of the Society of Instrument and Control Engineers of Japan, SICE 2019
Y2 - 10 September 2019 through 13 September 2019
ER -