Non-linear control algorithms for an unmanned surface vehicle
dc.contributor.author | sharma, sanjay | |
dc.contributor.author | Sutton, R | |
dc.contributor.author | Motwani, A | |
dc.contributor.author | Annamalai, A | |
dc.date.accessioned | 2015-10-15T11:20:48Z | |
dc.date.available | 2015-10-15T11:20:48Z | |
dc.date.issued | 2014-05 | |
dc.identifier.issn | 1475-0902 | |
dc.identifier.issn | 2041-3084 | |
dc.identifier.uri | http://hdl.handle.net/10026.1/3648 | |
dc.description.abstract |
<jats:p> Although intrinsically marine craft are known to exhibit non-linear dynamic characteristics, modern marine autopilot system designs continue to be developed based on both linear and non-linear control approaches. This article evaluates two novel non-linear autopilot designs based on non-linear local control network and non-linear model predictive control approaches to establish their effectiveness in terms of control activity expenditure, power consumption and mission duration length under similar operating conditions. From practical point of view, autopilot with less energy consumption would in reality provide the battery-powered vehicle with longer mission duration. The autopilot systems are used to control the non-linear yaw dynamics of an unmanned surface vehicle named Springer. The yaw dynamics of the vehicle being modelled using a multi-layer perceptron-type neural network. Simulation results showed that the autopilot based on local control network method performed better for Springer. Furthermore, on the whole, the local control network methodology can be regarded as a plausible paradigm for marine control system design. </jats:p> | |
dc.format.extent | 146-155 | |
dc.language | en | |
dc.language.iso | en | |
dc.publisher | SAGE Publications | |
dc.subject | Unmanned surface vehicle | |
dc.subject | autopilot design | |
dc.subject | non-linear model predictive control | |
dc.subject | local control network | |
dc.subject | genetic algorithm | |
dc.subject | neural networks | |
dc.title | Non-linear control algorithms for an unmanned surface vehicle | |
dc.type | journal-article | |
dc.type | Journal Article | |
plymouth.author-url | https://www.webofscience.com/api/gateway?GWVersion=2&SrcApp=PARTNER_APP&SrcAuth=LinksAMR&KeyUT=WOS:000336266300005&DestLinkType=FullRecord&DestApp=ALL_WOS&UsrCustomerID=11bb513d99f797142bcfeffcc58ea008 | |
plymouth.issue | 2 | |
plymouth.volume | 228 | |
plymouth.publication-status | Published | |
plymouth.journal | Proceedings of the Institution of Mechanical Engineers, Part M: Journal of Engineering for the Maritime Environment | |
dc.identifier.doi | 10.1177/1475090213503630 | |
plymouth.organisational-group | /Plymouth | |
plymouth.organisational-group | /Plymouth/Faculty of Science and Engineering | |
plymouth.organisational-group | /Plymouth/Faculty of Science and Engineering/School of Engineering, Computing and Mathematics | |
plymouth.organisational-group | /Plymouth/REF 2021 Researchers by UoA | |
plymouth.organisational-group | /Plymouth/REF 2021 Researchers by UoA/UoA12 Engineering | |
plymouth.organisational-group | /Plymouth/Research Groups | |
plymouth.organisational-group | /Plymouth/Research Groups/Marine Institute | |
plymouth.organisational-group | /Plymouth/Users by role | |
plymouth.organisational-group | /Plymouth/Users by role/Academics | |
dc.identifier.eissn | 2041-3084 | |
dc.rights.embargoperiod | Not known | |
rioxxterms.funder | Engineering and Physical Sciences Research Council | |
rioxxterms.identifier.project | An Intelligent Integrated Navigation and Autopilot System for Uninhabited Surface Vehicles | |
rioxxterms.versionofrecord | 10.1177/1475090213503630 | |
rioxxterms.licenseref.uri | http://www.rioxx.net/licenses/all-rights-reserved | |
rioxxterms.type | Journal Article/Review | |
plymouth.funder | An Intelligent Integrated Navigation and Autopilot System for Uninhabited Surface Vehicles::Engineering and Physical Sciences Research Council |