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

Design, Manufacturing And Engineering Management

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution book

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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)
Place of Publication	Piscataway, NJ
Publisher	IEEE
Number of pages	7
DOIs	https://doi.org/10.1109/ICMA.2017.8015991
Publication status	Published - 24 Aug 2017
Event	2017 IEEE International Conference on Mechatronics and Automation - Hayashi-cho, Takamatsu, 761-0396, Takamatsu, Japan Duration: 6 Aug 2017 → 9 Aug 2017 http://2017.ieee-icma.org/

Conference

Conference	2017 IEEE International Conference on Mechatronics and Automation
Abbreviated title	ICMA 2017
Country/Territory	Japan
City	Takamatsu
Period	6/08/17 → 9/08/17
Internet address	http://2017.ieee-icma.org/

Keywords

supercavitating vehicles
nonlinear guidance logic
trajectory tracking
genetic algorithm
parameter optimisation

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10.1109/ICMA.2017.8015991

Song-etal-IEEE-ICMA-2017-An-optimal-nonlinear-guidance-logic-for-the-trajectoryAccepted author manuscript, 557 KB

Cite this

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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 = "supercavitating vehicles, nonlinear guidance logic, trajectory tracking , genetic algorithm, parameter optimisation",

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

note = "{\textcopyright} 2017 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.; 2017 IEEE International Conference on Mechatronics and Automation, ICMA 2017 ; Conference date: 06-08-2017 Through 09-08-2017",

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AU - Song, Jia

AU - Gao, Ke

AU - Yang, Erfu

N1 - © 2017 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.

PY - 2017/8/24

Y1 - 2017/8/24

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 - supercavitating vehicles

KW - nonlinear guidance logic

KW - trajectory tracking

KW - genetic algorithm

KW - parameter optimisation

UR - http://2017.ieee-icma.org/

U2 - 10.1109/ICMA.2017.8015991

DO - 10.1109/ICMA.2017.8015991

M3 - Conference contribution book

BT - 2017 IEEE International Conference on Mechatronics and Automation (ICMA 2017)

PB - IEEE

CY - Piscataway, NJ

T2 - 2017 IEEE International Conference on Mechatronics and Automation

Y2 - 6 August 2017 through 9 August 2017

ER -

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

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