Please use this identifier to cite or link to this item: http://hdl.handle.net/10603/45676
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dc.coverage.spatialen_US
dc.date.accessioned2015-07-29T11:00:08Z-
dc.date.available2015-07-29T11:00:08Z-
dc.date.issued2015-07-29-
dc.identifier.urihttp://hdl.handle.net/10603/45676-
dc.description.abstractAll industrial processes have nonlinear dynamics Most control applications are based on linear models Linear models do not always give sufficient and adequate representation of the system Working with nonlinear models has given rise to a wide range of difficulties such as optimization problems slow processes and different approaches to guarantee stability In a multivariable non linear process mathematical modeling of physical systems has gained importance due to complex interactions within the system All parameters used in a model cannot be determined accurately Such processes are very often available in power plants chemical plants and in many other fields Major problem in a multivariable process is that loop interaction can arise and cause difficulties in feedback control design This problem can be solved using centralized like LQR Nonlinear Model Predictive control IMC fuzzy logic controller Model predictive controller etc or decentralized controllers like Proportional Integral Derivative controller Coefficient Diagram Method etc This thesis deals with nonlinear multiple interactive tank process whose performance is optimized by linear and nonlinear controllers First objective is to control the nonlinear Four Tank Process using PID CDM and MPC controllers for decentralized operation Objective number two is to control the nonlinear multiple Interactive Tank Process using MPC and NMPC controllers for centralized operations Simulated results are developed for nonlinear tank process by various control algorithms with satisfactory results The designed algorithm is fast enough and overcomes all limitations with respect to initial and final state values Feasibility and stability is ensured for both short as well as for long duration guaranteeing that the output reaches the set point Regarding reduction of time delay to reach final steady state with respect to set point is developed by Nonlinear Model Predictive control by tuning control parameters for multiple tank process using various MATLAB functions for all the conditions that are considered for evaluationen_US
dc.format.extenten_US
dc.languageEnglishen_US
dc.relationen_US
dc.rightsuniversityen_US
dc.titleINNOVATIVE APPROACH FOR STABILIZATION OF MULTIPLE INTERACTIVE TANK PROCESS WITH FEED FORWARD CONTROLLER AND FEEDBACK CONTROLLERen_US
dc.title.alternativeen_US
dc.creator.researcherSrinivasa Rao Poduguen_US
dc.subject.keywordMPC, NMPC, PID, CDM, stability, centralized, decentralizeden_US
dc.description.noteen_US
dc.contributor.guideDr.P.Subbaiahen_US
dc.publisher.placeChennaien_US
dc.publisher.universityDr. M.G.R. Educational and Research Instituteen_US
dc.publisher.institutionDepartment of Electronics and Communication Engineeringen_US
dc.date.registered12/02/2009en_US
dc.date.completed30/12/2014en_US
dc.date.awarded27/07/2015en_US
dc.format.dimensionsen_US
dc.format.accompanyingmaterialNoneen_US
dc.source.universityUniversityen_US
dc.type.degreePh.D.en_US
Appears in Departments:Department of Electronics and Communication Engineering

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01_title.pdfAttached File128.07 kBAdobe PDFView/Open
02_certificate.pdf210.39 kBAdobe PDFView/Open
03_toc,lot,lof&loa.pdf170.79 kBAdobe PDFView/Open
04_listofcorrections.pdf41.57 kBAdobe PDFView/Open
05_chapter 1.pdf535.26 kBAdobe PDFView/Open
06_chapter 2.pdf114.14 kBAdobe PDFView/Open
07_chapter 3.pdf548.01 kBAdobe PDFView/Open
08_chapter 4.pdf475.86 kBAdobe PDFView/Open
09_chapter 5.pdf1.8 MBAdobe PDFView/Open
10_chapter 6.pdf97.12 kBAdobe PDFView/Open
11_conclusion.pdf66.69 kBAdobe PDFView/Open
12_publications.pdf112.7 kBAdobe PDFView/Open
13_references.pdf119.42 kBAdobe PDFView/Open


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