In this paper, a surveillance system by multiple agents, which is called a multi-agent surveillance system, is studied. A surveillance area is given by an undirected connected graph. Then, the optimal control problem for multi-agent surveillance systems (the optimal surveillance problem) is to find trajectories of multiple agents that travel each node as evenly as possible. In our previous work, this problem is reduced to a mixed integer linear programming problem. However, the computation time for solving it exponentially grows with the number of agents. To overcome this technical issue, a new model predictive control method for multi-agent surveillance systems is proposed. First, a procedure of individual optimization, which is a kind of approximate solution methods, is proposed. Next, a method to improve the control performance is proposed. In addition, an event-triggering condition is also proposed. The effectiveness of the proposed method is presented by a numerical example.
Koichi KOBAYASHI
Hokkaido University
Mifuyu KIDO
Hokkaido University
Yuh YAMASHITA
Hokkaido University
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Koichi KOBAYASHI, Mifuyu KIDO, Yuh YAMASHITA, "Computationally Efficient Model Predictive Control for Multi-Agent Surveillance Systems" in IEICE TRANSACTIONS on Fundamentals,
vol. E102-A, no. 2, pp. 372-378, February 2019, doi: 10.1587/transfun.E102.A.372.
Abstract: In this paper, a surveillance system by multiple agents, which is called a multi-agent surveillance system, is studied. A surveillance area is given by an undirected connected graph. Then, the optimal control problem for multi-agent surveillance systems (the optimal surveillance problem) is to find trajectories of multiple agents that travel each node as evenly as possible. In our previous work, this problem is reduced to a mixed integer linear programming problem. However, the computation time for solving it exponentially grows with the number of agents. To overcome this technical issue, a new model predictive control method for multi-agent surveillance systems is proposed. First, a procedure of individual optimization, which is a kind of approximate solution methods, is proposed. Next, a method to improve the control performance is proposed. In addition, an event-triggering condition is also proposed. The effectiveness of the proposed method is presented by a numerical example.
URL: https://global.ieice.org/en_transactions/fundamentals/10.1587/transfun.E102.A.372/_p
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@ARTICLE{e102-a_2_372,
author={Koichi KOBAYASHI, Mifuyu KIDO, Yuh YAMASHITA, },
journal={IEICE TRANSACTIONS on Fundamentals},
title={Computationally Efficient Model Predictive Control for Multi-Agent Surveillance Systems},
year={2019},
volume={E102-A},
number={2},
pages={372-378},
abstract={In this paper, a surveillance system by multiple agents, which is called a multi-agent surveillance system, is studied. A surveillance area is given by an undirected connected graph. Then, the optimal control problem for multi-agent surveillance systems (the optimal surveillance problem) is to find trajectories of multiple agents that travel each node as evenly as possible. In our previous work, this problem is reduced to a mixed integer linear programming problem. However, the computation time for solving it exponentially grows with the number of agents. To overcome this technical issue, a new model predictive control method for multi-agent surveillance systems is proposed. First, a procedure of individual optimization, which is a kind of approximate solution methods, is proposed. Next, a method to improve the control performance is proposed. In addition, an event-triggering condition is also proposed. The effectiveness of the proposed method is presented by a numerical example.},
keywords={},
doi={10.1587/transfun.E102.A.372},
ISSN={1745-1337},
month={February},}
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TY - JOUR
TI - Computationally Efficient Model Predictive Control for Multi-Agent Surveillance Systems
T2 - IEICE TRANSACTIONS on Fundamentals
SP - 372
EP - 378
AU - Koichi KOBAYASHI
AU - Mifuyu KIDO
AU - Yuh YAMASHITA
PY - 2019
DO - 10.1587/transfun.E102.A.372
JO - IEICE TRANSACTIONS on Fundamentals
SN - 1745-1337
VL - E102-A
IS - 2
JA - IEICE TRANSACTIONS on Fundamentals
Y1 - February 2019
AB - In this paper, a surveillance system by multiple agents, which is called a multi-agent surveillance system, is studied. A surveillance area is given by an undirected connected graph. Then, the optimal control problem for multi-agent surveillance systems (the optimal surveillance problem) is to find trajectories of multiple agents that travel each node as evenly as possible. In our previous work, this problem is reduced to a mixed integer linear programming problem. However, the computation time for solving it exponentially grows with the number of agents. To overcome this technical issue, a new model predictive control method for multi-agent surveillance systems is proposed. First, a procedure of individual optimization, which is a kind of approximate solution methods, is proposed. Next, a method to improve the control performance is proposed. In addition, an event-triggering condition is also proposed. The effectiveness of the proposed method is presented by a numerical example.
ER -