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Rajinikanth, V.
- Design of Centralized PI Controller for Interacting Conical Tank System
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Authors
Affiliations
1 Caledonian College of Engineering, University College, Sultanate of Oman, Muscat, OM
2 St. Joseph’s College of Engineering, Chennai – 600119, Tamil Nadu, IN
1 Caledonian College of Engineering, University College, Sultanate of Oman, Muscat, OM
2 St. Joseph’s College of Engineering, Chennai – 600119, Tamil Nadu, IN
Source
Indian Journal of Science and Technology, Vol 9, No 12 (2016), Pagination:Abstract
Background/Objectives: The objective of this paper is to design centralised controller for liquid level in the two interacting conical tank system. Methods/Statistical analysis: Two Centralised Proportional and Integral (PI) controller tuning method (Davison method and Tanttu and Liestehto method) are used for simulation and implemented in real time process. Findings: Centralised PI controller reduces the interaction between the two interacting conical tank and improves the system performance. The performances are compared in terms of Integral Square Error (ISE) and Peak Overshoot. It is observed that Tanttu and Liestehto method produces better response than Davison method. Applications/Improvements: Level control in two interacting conical tank is used in chemical industries and water treatment plants.Keywords
: Centralised Controller, Multivariable System, Two Interacting Conical Tank SystemFull Text
- Image Multithresholding based on Kapur/Tsallis Entropy and Firefly Algorithm
Abstract Views :166 |
PDF Views:0
Authors
Affiliations
1 Caledonian College of Engineering, University College, Sultanate of Oman, Muscat, OM
2 St. Joseph’s College of Engineering, Chennai – 600119, Tamil Nadu, IN
1 Caledonian College of Engineering, University College, Sultanate of Oman, Muscat, OM
2 St. Joseph’s College of Engineering, Chennai – 600119, Tamil Nadu, IN
Source
Indian Journal of Science and Technology, Vol 9, No 12 (2016), Pagination:Abstract
Background/Objectives: In this paper, Firefly Algorithm (FA) based multilevel thresholding is proposed to segment the gray scale image by maximizing the entropy value. Methods/Statistical analysis: Better segmentation method gives appropriate threshold values to enhance the region of interest in the digital image. The entropy based methods, such as Kapur’s and Tsallis functions are chosen in this paper to segment the image. This work is implemented using the gray scale images obtained from Berkeley segmentation dataset. The FA assisted segmentation with entropy function is confirmed using the universal image superiority measures existing in the literature.Findings: Results of this simulation work show that Tsallis function offers better performance measure values, whereas the Kapur’s approach offers earlier convergence with comparatively lower CPU time. Applications/Improvements: Proposed method can be tested using other recent heuristic methods existing in the literature.Keywords
Entropy Value, Gray Scale Image, Kapur’s Function, Multithresholding, Tsallis FunctionFull Text