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http://hdl.handle.net/10603/379736
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DC Field | Value | Language |
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dc.coverage.spatial | ||
dc.date.accessioned | 2022-05-12T04:59:59Z | - |
dc.date.available | 2022-05-12T04:59:59Z | - |
dc.identifier.uri | http://hdl.handle.net/10603/379736 | - |
dc.description.abstract | This is an application-oriented thesis with the aim of developing new algorithms to develop controller within the framework of NCS. newlineScience and Technology advancements contributed significantly to the robustness and efficiency of the Control System. The Fourth Industrial Revolution introduced a holistic approach to the control system. The concept of the control system in-coagulation with communication network transformed to Networked Control System (NCS). Hence, Networked Control System implies a feedback control system in which the controller and the plant, are located at geographically distant locations but, via a communication network or the Internet, share the control signals from the controller to the plant and feedback signals from the sensor to controller. This approach improves the proximity and approachability of NCS. Its applications include remote polyhouse monitoring, remotely controlled defense operations, teleoperation or telesurgery and unmanned aerial vehicles are few to name. These applications rely on quick actuator or control signal manipulation to get the expected outcomes. A significant delay in the processing may have catastrophic consequences. newlineIn the literature, the problem of minimization of time delay is achieved through predictive approaches. The network induced delay is primarily; controller-to-actuator delay (and#964;_ca) and sensor-to-controller delay (and#964;_sc). When the controller directs a control signal to the plant through the network then the time taken by the control signal to reach the plant is termed as sensor-to-controller delay, the time taken by the plant to act accordingly to control signal is included in this delay. Whereas; the delay observed in receiving the feedback signal by the controller from the sensor through the network is termed as sensor-to-controller delay. It also includes the delay observed by the sensor to perceive the output from the plant. The maximum delay observed to stabilize the plant after receiving the control signal is called the deadtime. The deadtime inf | |
dc.format.extent | xxi,133p. | |
dc.language | English | |
dc.relation | ||
dc.rights | university | |
dc.title | Predictive Controller Based Delay Compensation Approaches in Networked Control System | |
dc.title.alternative | ||
dc.creator.researcher | Kumar, Ratish | |
dc.subject.keyword | Digital control systems | |
dc.subject.keyword | Electronic controllers | |
dc.subject.keyword | Engineering | |
dc.subject.keyword | Engineering and Technology | |
dc.subject.keyword | Engineering Electrical and Electronic | |
dc.subject.keyword | Estimation theory | |
dc.subject.keyword | Health and hygiene | |
dc.subject.keyword | Kalman filtering | |
dc.subject.keyword | Markov processes | |
dc.description.note | ||
dc.contributor.guide | Kumar, Rajiv and Nigam, Madhav Ji | |
dc.publisher.place | Solan | |
dc.publisher.university | Jaypee University of Information Technology, Solan | |
dc.publisher.institution | Department of Electronics and Communication Engineering | |
dc.date.registered | 2018 | |
dc.date.completed | 2021 | |
dc.date.awarded | 2022 | |
dc.format.dimensions | ||
dc.format.accompanyingmaterial | DVD | |
dc.source.university | University | |
dc.type.degree | Ph.D. | |
Appears in Departments: | Department of Electronics and Communication Engineering |
Files in This Item:
File | Description | Size | Format | |
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01_title.pdf | Attached File | 23.62 kB | Adobe PDF | View/Open |
02_declaration.pdf | 108.54 kB | Adobe PDF | View/Open | |
03_certificate.pdf | 98.31 kB | Adobe PDF | View/Open | |
04_acknowledgement.pdf | 130.27 kB | Adobe PDF | View/Open | |
05_content.pdf | 144.96 kB | Adobe PDF | View/Open | |
06_list of graph and table.pdf | 508.28 kB | Adobe PDF | View/Open | |
07_abstract.pdf | 78.9 kB | Adobe PDF | View/Open | |
08_chapter 1.pdf | 781.91 kB | Adobe PDF | View/Open | |
09_chapter 2.pdf | 100.59 kB | Adobe PDF | View/Open | |
10_chapter 3.pdf | 419.41 kB | Adobe PDF | View/Open | |
11_chapter 4.pdf | 828.36 kB | Adobe PDF | View/Open | |
12_chapter 5.pdf | 1.03 MB | Adobe PDF | View/Open | |
13_chapter 6.pdf | 1.85 MB | Adobe PDF | View/Open | |
14_chapter 7.pdf | 13 kB | Adobe PDF | View/Open | |
15_references.pdf | 221.54 kB | Adobe PDF | View/Open | |
16_appendices.pdf | 153.82 kB | Adobe PDF | View/Open | |
80_recommendation.pdf | 124.24 kB | Adobe PDF | View/Open |
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