Please use this identifier to cite or link to this item:
http://hdl.handle.net/10603/16439
Title: | Heuristic algorithm based identification and controller design for a class of unstable systems |
Researcher: | Rajinikanth V |
Guide(s): | Latha K |
Keywords: | Electrical engineering Heuristic algorithm |
Upload Date: | 27-Feb-2014 |
University: | Anna University |
Completed Date: | 01/11/2013 |
Abstract: | newline Nonlinear process loops such as continuous stirred tank reactor, newlineexothermic stirred reactors with back mixing, biochemical reactor, and newlinepolymerization reactors are extensively used in chemical industry to convert newlinethe raw materials into marketable products. To minimize the waste and to newlinemaximize the production rate, these chemical loops require best possible newlinecontrol actions. Optimizing the controller for these loops is a complex task newlinesince, they exhibit multiple steady states based on operating regions. Process newlinemodels with stable steady states are simple and conventional system newlineidentification and controller design procedures are sufficient to obtain better newlineresults. Design of controllers to stabilize chemical process loops and impart newlineadequate disturbance rejection is critical particularly when these loops are newlineoperating at unstable regions. System identification procedure is widely considered to develop newlineapproximated reduced order model from experimental data. This model is newlineemployed to design a controller. The conventional PID tuning methods newlineexisting for unstable processes are purely model dependent and the model newlinebased controller design procedure requires reduced order process models such newlineas First Order Plus Time Delay (FOPTD) or Second Order Plus Time Delay newline(SOPTD). The tuning procedure employed for one particular model may not provide a satisfactory response for other process models. For unstable system, newlineno unique methodology exists to design the controllers. newlineThe main objective of this research work is to implement heuristic newlinealgorithm based system identification and controller design procedures for a newlineclass of unstable process models. In this research work, heuristic algorithms newlinesuch as Particle Swarm Optimization (PSO), Bacterial Foraging Optimization newline(BFO), and hybrid algorithms are considered for system identification and newlinecontroller design manoeuvre. An empirical procedure is also proposed to newlineassign BFO parameters, to reduce the complexity in existing BFO algorithm. |
Pagination: | xxii, 171p. |
URI: | http://hdl.handle.net/10603/16439 |
Appears in Departments: | Faculty of Electrical and Electronics Engineering |
Files in This Item:
File | Description | Size | Format | |
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01_title.pdf | Attached File | 33.46 kB | Adobe PDF | View/Open |
02_certificate.pdf | 5.61 kB | Adobe PDF | View/Open | |
03_abstract.pdf | 10.55 kB | Adobe PDF | View/Open | |
04_acknowledgement.pdf | 6.5 kB | Adobe PDF | View/Open | |
05_contents.pdf | 42.95 kB | Adobe PDF | View/Open | |
06_chapter1.pdf | 255.86 kB | Adobe PDF | View/Open | |
07_chapter2.pdf | 49.55 kB | Adobe PDF | View/Open | |
08_chapter3.pdf | 347.46 kB | Adobe PDF | View/Open | |
09_chapter4.pdf | 139.32 kB | Adobe PDF | View/Open | |
10_chapter5.pdf | 350.06 kB | Adobe PDF | View/Open | |
11_chapter6.pdf | 350.06 kB | Adobe PDF | View/Open | |
12_chapter7.pdf | 231.76 kB | Adobe PDF | View/Open | |
13_chapter8.pdf | 14.54 kB | Adobe PDF | View/Open | |
14_appendix.pdf | 198.57 kB | Adobe PDF | View/Open | |
15_references.pdf | 38.66 kB | Adobe PDF | View/Open | |
16_vitae.pdf | 5.46 kB | Adobe PDF | View/Open |
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