Please use this identifier to cite or link to this item:
http://hdl.handle.net/10603/449787
Title: | Discrete laguerre function based distributed model predictive dynamic output consensus in linear multi agent systems with efficient triggering methods |
Researcher: | R, Resmi |
Guide(s): | S J, Mija and Jacob, Jeevamma |
Keywords: | Engineering and Technology Engineering Engineering Electrical and Electronic Multi-Agent Systems Dynamic Consensus |
University: | National Institute of Technology Calicut |
Completed Date: | 2022 |
Abstract: | A multi-agent system (MAS) is a network of autonomous agents that coordinate newlinewith each other to accomplish tasks together. MAS has emerged as a new topic newlinefor researchers and has wide range of applications and potential advantages in newlinemany fields, such as computer networks, communication engineering, formation newlinecontrol, search and rescue and multi-robot cooperation. In MAS, the agents usually newlineinteract with their neighbors to complete a complex task by exchanging cooperative newlineinformation. The communication patterns of the MAS are characterized by directed newlineor undirected graphs. newlineConsensus problem is a basic research topic in multi-agent coordination and the newlineconsensus of MAS is studied in this research. Among the numerous control protocols newlinefor MAS available in the literature, Model Predictive Control (MPC) is a superior newlinecontrol strategy because of its inherent capabilities to handle multivariate systems, newlinedisturbance rejection, input and output constraints, as well as cost minimization on newlinecontrol moves. Solving the consensus problem in a distributed fashion, where each newlineagent needs to have only its neighbors information is more appealing, leading to newlinedistributed MPC (DMPC). However, the implementation of conventional DMPC on newlinemultivariable systems with challenging process dynamics demands large prediction newlineand control horizons. This restricts its applicability due to excessive online computational newlineburden. Reducing the computational load is a necessity when it comes to newlinethe online implementation of controllers for MAS. Therefore, this research focuses newlineon model predictive control techniques that reduce the computational complexity of newlineonline optimization, when applied to solve the consensus problem of MAS.Incorporating newlineorthonormal discrete Laguerre functions in the consensus protocol is a solution newlineto the problem, which is seldom addressed for MAS in literature. newline |
Pagination: | |
URI: | http://hdl.handle.net/10603/449787 |
Appears in Departments: | ELECTRICAL ENGINEERING |
Files in This Item:
File | Description | Size | Format | |
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01_title.pdf | Attached File | 94.27 kB | Adobe PDF | View/Open |
02_prelim pages.pdf | 931.04 kB | Adobe PDF | View/Open | |
03_content.pdf | 70.21 kB | Adobe PDF | View/Open | |
04_abstract.pdf | 58.04 kB | Adobe PDF | View/Open | |
05_chapter 1.pdf | 95.97 kB | Adobe PDF | View/Open | |
06_chapter 2.pdf | 271.38 kB | Adobe PDF | View/Open | |
07_chapter 3.pdf | 660.89 kB | Adobe PDF | View/Open | |
08_chapter 4.pdf | 321.79 kB | Adobe PDF | View/Open | |
09_chapter 5.pdf | 327.42 kB | Adobe PDF | View/Open | |
10_chapter 6.pdf | 403.96 kB | Adobe PDF | View/Open | |
11_annexures.pdf | 102.42 kB | Adobe PDF | View/Open | |
80_recommendation.pdf | 102.94 kB | Adobe PDF | View/Open |
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