An optimal nonlinear guidance logic for the trajectory tracking of supercavitating vehicles

Jia Song; Ke Gao; Erfu Yang

doi:10.1109/ICMA.2017.8015991

An optimal nonlinear guidance logic for the trajectory tracking of supercavitating vehicles

Jia Song
, Ke Gao
, Erfu Yang

School of Astronautics

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

Abstract

Supercavitating vehicles (SV) are a class of high-speed autonomous underwater vessels. They present a great challenge in designing the guidance law in comparison with the traditional autonomous underwater vehicles. This is due to the fact that their constraints and working environment are much more complex. To tackle the above challenge, an optimal nonlinear midcourse guidance logic is proposed by considering the wake terminal guidance and the remote target attack tasks. The proposed guidance logic is optimized by using an efficient genetic algorithm to obtain its optimal parameters. The results from our simulation case study suggest that the proposed guidance logic can meet both the motion requirements and navigation constraints while effectively cooperating with the wake terminal guidance. Moreover, it has potential in reducing the energy consumption to significantly improve the overall vehicle energy efficiency.

Original language	English
Title of host publication	2017 IEEE International Conference on Mechatronics and Automation, ICMA 2017
Publisher	Institute of Electrical and Electronics Engineers Inc.
Pages	1221-1226
Number of pages	6
ISBN (Electronic)	9781509067572
DOIs	https://doi.org/10.1109/ICMA.2017.8015991
State	Published - 23 Aug 2017
Event	14th IEEE International Conference on Mechatronics and Automation, ICMA 2017 - Takamatsu, Japan Duration: 6 Aug 2017 → 9 Aug 2017

Publication series

Name	2017 IEEE International Conference on Mechatronics and Automation, ICMA 2017

Conference

Conference	14th IEEE International Conference on Mechatronics and Automation, ICMA 2017
Country/Territory	Japan
City	Takamatsu
Period	6/08/17 → 9/08/17

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

SDG 7 Affordable and Clean Energy

Keywords

Genetic Algorithm
Nonlinear Guidance Logic
Parameter Optimization
Supercavitating Vehicles
Trajectory Tracking

Access to Document

10.1109/ICMA.2017.8015991

Cite this

Song, J., Gao, K., & Yang, E. (2017). An optimal nonlinear guidance logic for the trajectory tracking of supercavitating vehicles. In 2017 IEEE International Conference on Mechatronics and Automation, ICMA 2017 (pp. 1221-1226). Article 8015991 (2017 IEEE International Conference on Mechatronics and Automation, ICMA 2017). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/ICMA.2017.8015991

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title = "An optimal nonlinear guidance logic for the trajectory tracking of supercavitating vehicles",

abstract = "Supercavitating vehicles (SV) are a class of high-speed autonomous underwater vessels. They present a great challenge in designing the guidance law in comparison with the traditional autonomous underwater vehicles. This is due to the fact that their constraints and working environment are much more complex. To tackle the above challenge, an optimal nonlinear midcourse guidance logic is proposed by considering the wake terminal guidance and the remote target attack tasks. The proposed guidance logic is optimized by using an efficient genetic algorithm to obtain its optimal parameters. The results from our simulation case study suggest that the proposed guidance logic can meet both the motion requirements and navigation constraints while effectively cooperating with the wake terminal guidance. Moreover, it has potential in reducing the energy consumption to significantly improve the overall vehicle energy efficiency.",

keywords = "Genetic Algorithm, Nonlinear Guidance Logic, Parameter Optimization, Supercavitating Vehicles, Trajectory Tracking",

author = "Jia Song and Ke Gao and Erfu Yang",

note = "Publisher Copyright: {\textcopyright} 2017 IEEE.; 14th IEEE International Conference on Mechatronics and Automation, ICMA 2017 ; Conference date: 06-08-2017 Through 09-08-2017",

year = "2017",

month = aug,

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doi = "10.1109/ICMA.2017.8015991",

language = "英语",

series = "2017 IEEE International Conference on Mechatronics and Automation, ICMA 2017",

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Song, J, Gao, K & Yang, E 2017, An optimal nonlinear guidance logic for the trajectory tracking of supercavitating vehicles. in 2017 IEEE International Conference on Mechatronics and Automation, ICMA 2017., 8015991, 2017 IEEE International Conference on Mechatronics and Automation, ICMA 2017, Institute of Electrical and Electronics Engineers Inc., pp. 1221-1226, 14th IEEE International Conference on Mechatronics and Automation, ICMA 2017, Takamatsu, Japan, 6/08/17. https://doi.org/10.1109/ICMA.2017.8015991

An optimal nonlinear guidance logic for the trajectory tracking of supercavitating vehicles. / Song, Jia; Gao, Ke; Yang, Erfu.
2017 IEEE International Conference on Mechatronics and Automation, ICMA 2017. Institute of Electrical and Electronics Engineers Inc., 2017. p. 1221-1226 8015991 (2017 IEEE International Conference on Mechatronics and Automation, ICMA 2017).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

TY - GEN

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AU - Gao, Ke

AU - Yang, Erfu

PY - 2017/8/23

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N2 - Supercavitating vehicles (SV) are a class of high-speed autonomous underwater vessels. They present a great challenge in designing the guidance law in comparison with the traditional autonomous underwater vehicles. This is due to the fact that their constraints and working environment are much more complex. To tackle the above challenge, an optimal nonlinear midcourse guidance logic is proposed by considering the wake terminal guidance and the remote target attack tasks. The proposed guidance logic is optimized by using an efficient genetic algorithm to obtain its optimal parameters. The results from our simulation case study suggest that the proposed guidance logic can meet both the motion requirements and navigation constraints while effectively cooperating with the wake terminal guidance. Moreover, it has potential in reducing the energy consumption to significantly improve the overall vehicle energy efficiency.

AB - Supercavitating vehicles (SV) are a class of high-speed autonomous underwater vessels. They present a great challenge in designing the guidance law in comparison with the traditional autonomous underwater vehicles. This is due to the fact that their constraints and working environment are much more complex. To tackle the above challenge, an optimal nonlinear midcourse guidance logic is proposed by considering the wake terminal guidance and the remote target attack tasks. The proposed guidance logic is optimized by using an efficient genetic algorithm to obtain its optimal parameters. The results from our simulation case study suggest that the proposed guidance logic can meet both the motion requirements and navigation constraints while effectively cooperating with the wake terminal guidance. Moreover, it has potential in reducing the energy consumption to significantly improve the overall vehicle energy efficiency.

KW - Genetic Algorithm

KW - Nonlinear Guidance Logic

KW - Parameter Optimization

KW - Supercavitating Vehicles

KW - Trajectory Tracking

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M3 - 会议稿件

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SP - 1221

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BT - 2017 IEEE International Conference on Mechatronics and Automation, ICMA 2017

PB - Institute of Electrical and Electronics Engineers Inc.

T2 - 14th IEEE International Conference on Mechatronics and Automation, ICMA 2017

Y2 - 6 August 2017 through 9 August 2017

ER -

Song J, Gao K, Yang E. An optimal nonlinear guidance logic for the trajectory tracking of supercavitating vehicles. In 2017 IEEE International Conference on Mechatronics and Automation, ICMA 2017. Institute of Electrical and Electronics Engineers Inc. 2017. p. 1221-1226. 8015991. (2017 IEEE International Conference on Mechatronics and Automation, ICMA 2017). doi: 10.1109/ICMA.2017.8015991

An optimal nonlinear guidance logic for the trajectory tracking of supercavitating vehicles

Abstract

Publication series

Conference

UN SDGs

Keywords

Access to Document

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