Abstract
A novel distributed control scheme, called one-step predictive finite memory control (OPFMC), is proposed for multiple unmanned aerial vehicles (UAVs). The OPFMC is constructed through a controller gain obtained from a distributed system considering multiple UAVs. Furthermore, the OPFMC is developed with the estimated states acquired through a gain that minimizes a newly introduced cost function: Frobenius norm, and from two consecutive processes with differently defined stacked measurements by introducing a weight parameter in the horizon bank that represents a finite memory structure. Since unexpected disturbance or unknown noise is compensated by the weight parameter, OPFMC shows robustness in the presence of unexpected disturbances or unknown noise. The robust performance and fast convergence of the proposed control scheme under disturbance or noise is demonstrated through experimental results.
| Original language | English |
|---|---|
| Title of host publication | 2019 IEEE International Conference on Systems, Man and Cybernetics, SMC 2019 |
| Publisher | Institute of Electrical and Electronics Engineers Inc. |
| Pages | 1769-1774 |
| Number of pages | 6 |
| ISBN (Electronic) | 9781728145693 |
| DOIs | |
| Publication status | Published - 2019 Oct |
| Event | 2019 IEEE International Conference on Systems, Man and Cybernetics, SMC 2019 - Bari, Italy Duration: 2019 Oct 6 → 2019 Oct 9 |
Publication series
| Name | Conference Proceedings - IEEE International Conference on Systems, Man and Cybernetics |
|---|---|
| Volume | 2019-October |
| ISSN (Print) | 1062-922X |
Conference
| Conference | 2019 IEEE International Conference on Systems, Man and Cybernetics, SMC 2019 |
|---|---|
| Country | Italy |
| City | Bari |
| Period | 19/10/6 → 19/10/9 |
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Keywords
- Distributed system
- Finite memory structure
- Multiple unmanned aerial vehicles (UAVs)
- Robustness
- Unbiasedness
ASJC Scopus subject areas
- Electrical and Electronic Engineering
- Control and Systems Engineering
- Human-Computer Interaction
Cite this
Distributed control for multiple unmanned aerial vehicles with one-step predictive finite memory control. / Kang, Hyun Ho; Lee, Sang Su; Ahn, Choon Ki.
2019 IEEE International Conference on Systems, Man and Cybernetics, SMC 2019. Institute of Electrical and Electronics Engineers Inc., 2019. p. 1769-1774 8914197 (Conference Proceedings - IEEE International Conference on Systems, Man and Cybernetics; Vol. 2019-October).Research output: Chapter in Book/Report/Conference proceeding › Conference contribution
}
TY - GEN
T1 - Distributed control for multiple unmanned aerial vehicles with one-step predictive finite memory control
AU - Kang, Hyun Ho
AU - Lee, Sang Su
AU - Ahn, Choon Ki
PY - 2019/10
Y1 - 2019/10
N2 - A novel distributed control scheme, called one-step predictive finite memory control (OPFMC), is proposed for multiple unmanned aerial vehicles (UAVs). The OPFMC is constructed through a controller gain obtained from a distributed system considering multiple UAVs. Furthermore, the OPFMC is developed with the estimated states acquired through a gain that minimizes a newly introduced cost function: Frobenius norm, and from two consecutive processes with differently defined stacked measurements by introducing a weight parameter in the horizon bank that represents a finite memory structure. Since unexpected disturbance or unknown noise is compensated by the weight parameter, OPFMC shows robustness in the presence of unexpected disturbances or unknown noise. The robust performance and fast convergence of the proposed control scheme under disturbance or noise is demonstrated through experimental results.
AB - A novel distributed control scheme, called one-step predictive finite memory control (OPFMC), is proposed for multiple unmanned aerial vehicles (UAVs). The OPFMC is constructed through a controller gain obtained from a distributed system considering multiple UAVs. Furthermore, the OPFMC is developed with the estimated states acquired through a gain that minimizes a newly introduced cost function: Frobenius norm, and from two consecutive processes with differently defined stacked measurements by introducing a weight parameter in the horizon bank that represents a finite memory structure. Since unexpected disturbance or unknown noise is compensated by the weight parameter, OPFMC shows robustness in the presence of unexpected disturbances or unknown noise. The robust performance and fast convergence of the proposed control scheme under disturbance or noise is demonstrated through experimental results.
KW - Distributed system
KW - Finite memory structure
KW - Multiple unmanned aerial vehicles (UAVs)
KW - Robustness
KW - Unbiasedness
UR - http://www.scopus.com/inward/record.url?scp=85076770435&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85076770435&partnerID=8YFLogxK
U2 - 10.1109/SMC.2019.8914197
DO - 10.1109/SMC.2019.8914197
M3 - Conference contribution
AN - SCOPUS:85076770435
T3 - Conference Proceedings - IEEE International Conference on Systems, Man and Cybernetics
SP - 1769
EP - 1774
BT - 2019 IEEE International Conference on Systems, Man and Cybernetics, SMC 2019
PB - Institute of Electrical and Electronics Engineers Inc.
ER -