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Event-Triggered Adaptive Neural Network Controller in a Cyber-Physical Framework
The importance of remotely placed controller in a cyber space with sensor-controller-actuator network has increased significantly in industrial, defense, and surveillance sector. Such network has large amount of sensor and controller data. A time-triggered control technique may generate redundant co...
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Published in: | IEEE transactions on industrial informatics 2019-04, Vol.15 (4), p.2101-2111 |
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description | The importance of remotely placed controller in a cyber space with sensor-controller-actuator network has increased significantly in industrial, defense, and surveillance sector. Such network has large amount of sensor and controller data. A time-triggered control technique may generate redundant control signals and put unnecessary data on network. Therefore, an event-triggered adaptive controller that generates control action at required instants using state- and error-based conditions has been developed in this paper. A data transmission framework has also been designed in this paper that addresses network delay and packet losses. The proposed controller-communication methodology has been validated through two case studies, first, temperature tracking for heating ventilation and air conditioning system and, second, real-time path tracking by automated guided vehicle. The proposed methodology has also been duly compared with its time-triggered counterpart. The control updates are reduced to approximately 41% and 64% in the two case studies, respectively. The experimental results also prove the designed controller to be efficient when compared with event-triggered incremental PID controller using the same data transmission framework. |
doi_str_mv | 10.1109/TII.2018.2861904 |
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Such network has large amount of sensor and controller data. A time-triggered control technique may generate redundant control signals and put unnecessary data on network. Therefore, an event-triggered adaptive controller that generates control action at required instants using state- and error-based conditions has been developed in this paper. A data transmission framework has also been designed in this paper that addresses network delay and packet losses. The proposed controller-communication methodology has been validated through two case studies, first, temperature tracking for heating ventilation and air conditioning system and, second, real-time path tracking by automated guided vehicle. The proposed methodology has also been duly compared with its time-triggered counterpart. The control updates are reduced to approximately 41% and 64% in the two case studies, respectively. 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Such network has large amount of sensor and controller data. A time-triggered control technique may generate redundant control signals and put unnecessary data on network. Therefore, an event-triggered adaptive controller that generates control action at required instants using state- and error-based conditions has been developed in this paper. A data transmission framework has also been designed in this paper that addresses network delay and packet losses. The proposed controller-communication methodology has been validated through two case studies, first, temperature tracking for heating ventilation and air conditioning system and, second, real-time path tracking by automated guided vehicle. The proposed methodology has also been duly compared with its time-triggered counterpart. The control updates are reduced to approximately 41% and 64% in the two case studies, respectively. The experimental results also prove the designed controller to be efficient when compared with event-triggered incremental PID controller using the same data transmission framework.</description><subject>Actuators</subject><subject>Adaptive control</subject><subject>Adaptive neural network (NN) controller</subject><subject>Adaptive systems</subject><subject>Air conditioners</subject><subject>Air conditioning</subject><subject>Artificial neural networks</subject><subject>Automated guided vehicles</subject><subject>Case studies</subject><subject>Control systems design</subject><subject>Controllers</subject><subject>cyber–physical system</subject><subject>Data communication</subject><subject>Data transmission</subject><subject>Defense industry</subject><subject>delay</subject><subject>Delays</subject><subject>event-triggered controller</subject><subject>incremental PID controller</subject><subject>Internet</subject><subject>Neural networks</subject><subject>Path tracking</subject><subject>Proportional integral derivative</subject><subject>Remote control</subject><subject>Remote sensors</subject><subject>System dynamics</subject><subject>Uncertainty</subject><subject>Ventilation</subject><issn>1551-3203</issn><issn>1941-0050</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2019</creationdate><recordtype>article</recordtype><recordid>eNo9kE1PwkAQhjdGExG9m3hp4rk4sx_9OJIGlYQoh943y3aKxdLibsHw710C8fTO4XlnMg9jjwgTRMhfyvl8wgGzCc8SzEFesRHmEmMABddhVgpjwUHcsjvvNwAiBZGP2HJ2oG6IS9es1-SoiqaV2Q3NgaIP2jvThhh-e_cdFX03uL5tyUVNF5moOK7Ixcuvo29swF6d2dIJvGc3tWk9PVxyzMrXWVm8x4vPt3kxXcSW5zjEGaxSy7PKKBJkJNBKVNZWPMtVLataABhrABK0ssqtwjQRAhPkGFApjRiz5_Panet_9uQHven3rgsXNQ9fShAilYGCM2Vd772jWu9cszXuqBH0SZsO2vRJm75oC5Wnc6Uhon88k1yCkuIPquFoLQ</recordid><startdate>20190401</startdate><enddate>20190401</enddate><creator>Kar, Aniket K.</creator><creator>Dhar, Narendra Kumar</creator><creator>Verma, Nishchal K.</creator><general>IEEE</general><general>The Institute of Electrical and Electronics Engineers, Inc. (IEEE)</general><scope>97E</scope><scope>RIA</scope><scope>RIE</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>7SC</scope><scope>7SP</scope><scope>8FD</scope><scope>JQ2</scope><scope>L7M</scope><scope>L~C</scope><scope>L~D</scope><orcidid>https://orcid.org/0000-0002-5343-5812</orcidid><orcidid>https://orcid.org/0000-0001-8752-5616</orcidid><orcidid>https://orcid.org/0000-0002-1530-7430</orcidid></search><sort><creationdate>20190401</creationdate><title>Event-Triggered Adaptive Neural Network Controller in a Cyber-Physical Framework</title><author>Kar, Aniket K. ; Dhar, Narendra Kumar ; Verma, Nishchal K.</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c291t-80b7c28da5e3ea40eb3dccd2895f4df300aca0061c4d9c5176331612140e44a3</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2019</creationdate><topic>Actuators</topic><topic>Adaptive control</topic><topic>Adaptive neural network (NN) controller</topic><topic>Adaptive systems</topic><topic>Air conditioners</topic><topic>Air conditioning</topic><topic>Artificial neural networks</topic><topic>Automated guided vehicles</topic><topic>Case studies</topic><topic>Control systems design</topic><topic>Controllers</topic><topic>cyber–physical system</topic><topic>Data communication</topic><topic>Data transmission</topic><topic>Defense industry</topic><topic>delay</topic><topic>Delays</topic><topic>event-triggered controller</topic><topic>incremental PID controller</topic><topic>Internet</topic><topic>Neural networks</topic><topic>Path tracking</topic><topic>Proportional integral derivative</topic><topic>Remote control</topic><topic>Remote sensors</topic><topic>System dynamics</topic><topic>Uncertainty</topic><topic>Ventilation</topic><toplevel>online_resources</toplevel><creatorcontrib>Kar, Aniket K.</creatorcontrib><creatorcontrib>Dhar, Narendra Kumar</creatorcontrib><creatorcontrib>Verma, Nishchal K.</creatorcontrib><collection>IEEE All-Society Periodicals Package (ASPP) 2005-present</collection><collection>IEEE All-Society Periodicals Package (ASPP) 1998–Present</collection><collection>IEEE/IET Electronic Library (IEL)</collection><collection>CrossRef</collection><collection>Computer and Information Systems Abstracts</collection><collection>Electronics & Communications Abstracts</collection><collection>Technology 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>IEEE transactions on industrial informatics</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Kar, Aniket K.</au><au>Dhar, Narendra Kumar</au><au>Verma, Nishchal K.</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Event-Triggered Adaptive Neural Network Controller in a Cyber-Physical Framework</atitle><jtitle>IEEE transactions on industrial informatics</jtitle><stitle>TII</stitle><date>2019-04-01</date><risdate>2019</risdate><volume>15</volume><issue>4</issue><spage>2101</spage><epage>2111</epage><pages>2101-2111</pages><issn>1551-3203</issn><eissn>1941-0050</eissn><coden>ITIICH</coden><abstract>The importance of remotely placed controller in a cyber space with sensor-controller-actuator network has increased significantly in industrial, defense, and surveillance sector. 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subjects | Actuators Adaptive control Adaptive neural network (NN) controller Adaptive systems Air conditioners Air conditioning Artificial neural networks Automated guided vehicles Case studies Control systems design Controllers cyber–physical system Data communication Data transmission Defense industry delay Delays event-triggered controller incremental PID controller Internet Neural networks Path tracking Proportional integral derivative Remote control Remote sensors System dynamics Uncertainty Ventilation |
title | Event-Triggered Adaptive Neural Network Controller in a Cyber-Physical Framework |
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