Management and optimisation of chaotic supply chain system using adaptive sliding mode control algorithm
This paper deals with adaptive super-twisting (STW) sliding mode control (SMC) algorithm to manage chaotic supply chain system. A multi-echelon supply chain system having parametric perturbations and disturbances is presented to demonstrate chaotic nonlinear dynamical behaviours. When changing input...
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Veröffentlicht in: | International journal of production research 2021-05, Vol.59 (9), p.2571-2587 |
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description | This paper deals with adaptive super-twisting (STW) sliding mode control (SMC) algorithm to manage chaotic supply chain system. A multi-echelon supply chain system having parametric perturbations and disturbances is presented to demonstrate chaotic nonlinear dynamical behaviours. When changing input variables slightly in the supply chain system, the predicted outputs will be completely different due to chaotic behaviours with bifurcation. In addition, various uncertainties along with exogenous disturbances make the system dynamics more complex to manage as they propagate both upstream and downstream of the supply chain networks. Particularly, the adaptive STW SMC algorithm has been designed for chaos suppression and synchronisation of the supply chain system. Next, the robust control algorithm with adaptive law for the closed-loop system has been proved by using Lyapunov stability theorem. Then, extensive numerical simulations are conducted to demonstrate the validity of the active control synthesis for optimal operations management of chaotic supply chain networks. The control algorithm based on system theory provides satisfactory performance on achieving chaos suppression and synchronisation of the chaotic supply system. The control system theory can be expanded into new integration software applications for operations management of supply chain networks. Finally, the presented control synthesis with dynamical analysis is essential for strategic decision-makers in the modern supply chain management. |
doi_str_mv | 10.1080/00207543.2020.1735662 |
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A multi-echelon supply chain system having parametric perturbations and disturbances is presented to demonstrate chaotic nonlinear dynamical behaviours. When changing input variables slightly in the supply chain system, the predicted outputs will be completely different due to chaotic behaviours with bifurcation. In addition, various uncertainties along with exogenous disturbances make the system dynamics more complex to manage as they propagate both upstream and downstream of the supply chain networks. Particularly, the adaptive STW SMC algorithm has been designed for chaos suppression and synchronisation of the supply chain system. Next, the robust control algorithm with adaptive law for the closed-loop system has been proved by using Lyapunov stability theorem. Then, extensive numerical simulations are conducted to demonstrate the validity of the active control synthesis for optimal operations management of chaotic supply chain networks. The control algorithm based on system theory provides satisfactory performance on achieving chaos suppression and synchronisation of the chaotic supply system. The control system theory can be expanded into new integration software applications for operations management of supply chain networks. Finally, the presented control synthesis with dynamical analysis is essential for strategic decision-makers in the modern supply chain management.</description><identifier>ISSN: 0020-7543</identifier><identifier>EISSN: 1366-588X</identifier><identifier>DOI: 10.1080/00207543.2020.1735662</identifier><language>eng</language><publisher>London: Taylor & Francis</publisher><subject>Active control ; Adaptive algorithms ; Adaptive control ; adaptive sliding mode control ; Applications programs ; bullwhip effect ; business profitability ; Chaos theory ; chaotic dynamics ; Control algorithms ; Control theory ; Decision analysis ; Decision making ; Disturbances ; Electronic procurement ; Feedback control ; Lyapunov stability ; multi-echelon supply chain ; Networks ; Operations management ; Optimization ; Perturbation ; Robust control ; Sliding mode control ; Supply chains ; suppression ; synchronisation ; Synchronism ; Synthesis ; System dynamics ; System theory ; Systems theory</subject><ispartof>International journal of production research, 2021-05, Vol.59 (9), p.2571-2587</ispartof><rights>2020 Informa UK Limited, trading as Taylor & Francis Group 2020</rights><rights>2020 Informa UK Limited, trading as Taylor & Francis Group</rights><lds50>peer_reviewed</lds50><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c395t-1546841980221ac32584df99807cc99a714419720b293956a63873390ff062f23</citedby><cites>FETCH-LOGICAL-c395t-1546841980221ac32584df99807cc99a714419720b293956a63873390ff062f23</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://www.tandfonline.com/doi/pdf/10.1080/00207543.2020.1735662$$EPDF$$P50$$Ginformaworld$$H</linktopdf><linktohtml>$$Uhttps://www.tandfonline.com/doi/full/10.1080/00207543.2020.1735662$$EHTML$$P50$$Ginformaworld$$H</linktohtml><link.rule.ids>314,776,780,27901,27902,59620,60409</link.rule.ids></links><search><creatorcontrib>Xu, Xiao</creatorcontrib><creatorcontrib>Lee, Sang-Do</creatorcontrib><creatorcontrib>Kim, Hwan-Seong</creatorcontrib><creatorcontrib>You, Sam-Sang</creatorcontrib><title>Management and optimisation of chaotic supply chain system using adaptive sliding mode control algorithm</title><title>International journal of production research</title><description>This paper deals with adaptive super-twisting (STW) sliding mode control (SMC) algorithm to manage chaotic supply chain system. A multi-echelon supply chain system having parametric perturbations and disturbances is presented to demonstrate chaotic nonlinear dynamical behaviours. When changing input variables slightly in the supply chain system, the predicted outputs will be completely different due to chaotic behaviours with bifurcation. In addition, various uncertainties along with exogenous disturbances make the system dynamics more complex to manage as they propagate both upstream and downstream of the supply chain networks. Particularly, the adaptive STW SMC algorithm has been designed for chaos suppression and synchronisation of the supply chain system. Next, the robust control algorithm with adaptive law for the closed-loop system has been proved by using Lyapunov stability theorem. Then, extensive numerical simulations are conducted to demonstrate the validity of the active control synthesis for optimal operations management of chaotic supply chain networks. The control algorithm based on system theory provides satisfactory performance on achieving chaos suppression and synchronisation of the chaotic supply system. The control system theory can be expanded into new integration software applications for operations management of supply chain networks. Finally, the presented control synthesis with dynamical analysis is essential for strategic decision-makers in the modern supply chain management.</description><subject>Active control</subject><subject>Adaptive algorithms</subject><subject>Adaptive control</subject><subject>adaptive sliding mode control</subject><subject>Applications programs</subject><subject>bullwhip effect</subject><subject>business profitability</subject><subject>Chaos theory</subject><subject>chaotic dynamics</subject><subject>Control algorithms</subject><subject>Control theory</subject><subject>Decision analysis</subject><subject>Decision making</subject><subject>Disturbances</subject><subject>Electronic procurement</subject><subject>Feedback control</subject><subject>Lyapunov stability</subject><subject>multi-echelon supply chain</subject><subject>Networks</subject><subject>Operations management</subject><subject>Optimization</subject><subject>Perturbation</subject><subject>Robust control</subject><subject>Sliding mode control</subject><subject>Supply chains</subject><subject>suppression</subject><subject>synchronisation</subject><subject>Synchronism</subject><subject>Synthesis</subject><subject>System dynamics</subject><subject>System theory</subject><subject>Systems theory</subject><issn>0020-7543</issn><issn>1366-588X</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2021</creationdate><recordtype>article</recordtype><recordid>eNp9kEtvGyEURlGVSnXc_oRKSFmPy2N4zK6RlaSVHHXTSt4hyoCNNQMTYBL535eRU2UXNnDhHC58AHzFaIORRN8QIkiwlm5IXWywoIxz8gGsMOW8YVLur8BqYZoF-gSucz6hOphsV-D4qIM-2NGGAnXoYZyKH33WxccAo4PmqGPxBuZ5mobzUvoA8zkXO8I5-3CAutfVebYwD75fNsbYW2hiKCkOUA-HmHw5jp_BR6eHbL-8zmvw5_7u9_ZHs_v18HN7u2sM7VhpMGu5bHEnESFYG0rqK3vX1VoY03Va4LaeCoL-kq4KXHMqBaUdcg5x4ghdg5vLvVOKT7PNRZ3inEJtqQgjWLakE7xS7EKZFHNO1qkp-VGns8JILaGq_6GqJVT1Gmr14MWz9YM-v1mCSdEShvYV-X5BfHAxjfolpqFXRZ-HmFzSwVSNvt_lHxDnh-A</recordid><startdate>20210503</startdate><enddate>20210503</enddate><creator>Xu, Xiao</creator><creator>Lee, Sang-Do</creator><creator>Kim, Hwan-Seong</creator><creator>You, Sam-Sang</creator><general>Taylor & Francis</general><general>Taylor & Francis LLC</general><scope>OQ6</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>7SC</scope><scope>8FD</scope><scope>F28</scope><scope>FR3</scope><scope>JQ2</scope><scope>L7M</scope><scope>L~C</scope><scope>L~D</scope></search><sort><creationdate>20210503</creationdate><title>Management and optimisation of chaotic supply chain system using adaptive sliding mode control algorithm</title><author>Xu, Xiao ; Lee, Sang-Do ; Kim, Hwan-Seong ; You, Sam-Sang</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c395t-1546841980221ac32584df99807cc99a714419720b293956a63873390ff062f23</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2021</creationdate><topic>Active control</topic><topic>Adaptive algorithms</topic><topic>Adaptive control</topic><topic>adaptive sliding mode control</topic><topic>Applications programs</topic><topic>bullwhip effect</topic><topic>business profitability</topic><topic>Chaos theory</topic><topic>chaotic dynamics</topic><topic>Control algorithms</topic><topic>Control theory</topic><topic>Decision analysis</topic><topic>Decision making</topic><topic>Disturbances</topic><topic>Electronic procurement</topic><topic>Feedback control</topic><topic>Lyapunov stability</topic><topic>multi-echelon supply chain</topic><topic>Networks</topic><topic>Operations management</topic><topic>Optimization</topic><topic>Perturbation</topic><topic>Robust control</topic><topic>Sliding mode control</topic><topic>Supply chains</topic><topic>suppression</topic><topic>synchronisation</topic><topic>Synchronism</topic><topic>Synthesis</topic><topic>System dynamics</topic><topic>System theory</topic><topic>Systems theory</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Xu, Xiao</creatorcontrib><creatorcontrib>Lee, Sang-Do</creatorcontrib><creatorcontrib>Kim, Hwan-Seong</creatorcontrib><creatorcontrib>You, Sam-Sang</creatorcontrib><collection>ECONIS</collection><collection>CrossRef</collection><collection>Computer and Information Systems Abstracts</collection><collection>Technology Research Database</collection><collection>ANTE: Abstracts in New Technology & Engineering</collection><collection>Engineering Research Database</collection><collection>ProQuest Computer Science Collection</collection><collection>Advanced Technologies Database with Aerospace</collection><collection>Computer and Information Systems Abstracts Academic</collection><collection>Computer and Information Systems Abstracts Professional</collection><jtitle>International journal of production research</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Xu, Xiao</au><au>Lee, Sang-Do</au><au>Kim, Hwan-Seong</au><au>You, Sam-Sang</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Management and optimisation of chaotic supply chain system using adaptive sliding mode control algorithm</atitle><jtitle>International journal of production research</jtitle><date>2021-05-03</date><risdate>2021</risdate><volume>59</volume><issue>9</issue><spage>2571</spage><epage>2587</epage><pages>2571-2587</pages><issn>0020-7543</issn><eissn>1366-588X</eissn><abstract>This paper deals with adaptive super-twisting (STW) sliding mode control (SMC) algorithm to manage chaotic supply chain system. A multi-echelon supply chain system having parametric perturbations and disturbances is presented to demonstrate chaotic nonlinear dynamical behaviours. When changing input variables slightly in the supply chain system, the predicted outputs will be completely different due to chaotic behaviours with bifurcation. In addition, various uncertainties along with exogenous disturbances make the system dynamics more complex to manage as they propagate both upstream and downstream of the supply chain networks. Particularly, the adaptive STW SMC algorithm has been designed for chaos suppression and synchronisation of the supply chain system. Next, the robust control algorithm with adaptive law for the closed-loop system has been proved by using Lyapunov stability theorem. Then, extensive numerical simulations are conducted to demonstrate the validity of the active control synthesis for optimal operations management of chaotic supply chain networks. The control algorithm based on system theory provides satisfactory performance on achieving chaos suppression and synchronisation of the chaotic supply system. The control system theory can be expanded into new integration software applications for operations management of supply chain networks. Finally, the presented control synthesis with dynamical analysis is essential for strategic decision-makers in the modern supply chain management.</abstract><cop>London</cop><pub>Taylor & Francis</pub><doi>10.1080/00207543.2020.1735662</doi><tpages>17</tpages></addata></record> |
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subjects | Active control Adaptive algorithms Adaptive control adaptive sliding mode control Applications programs bullwhip effect business profitability Chaos theory chaotic dynamics Control algorithms Control theory Decision analysis Decision making Disturbances Electronic procurement Feedback control Lyapunov stability multi-echelon supply chain Networks Operations management Optimization Perturbation Robust control Sliding mode control Supply chains suppression synchronisation Synchronism Synthesis System dynamics System theory Systems theory |
title | Management and optimisation of chaotic supply chain system using adaptive sliding mode control algorithm |
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