Pub Date : 2020-09-05DOI: 10.1109/ICCE50343.2020.9290504
Ritwik Raha, Arpan Sengupta, Supriya Dhabal
This paper proposes a novel algorithm for the fusion of medical images using a modified Pulse Coupled Neural Network(PCNN) optimized by the Whale Optimization Algorithm(WOA). In this proposed algorithm the two images are passed through the WOA which computes the necessary parameters for the PCNN feature extractor through a multi-criteria fitness function. The features thus extracted are then used to fuse the images. The resultant fused image is judged by evaluating the entropy, Mutual Information (MI), Structural Similarity (SSIM), etc. as well as a specialized performance metric called feature mutual information.
{"title":"Medical Image Fusion using PCNN Optimized by Whale Optimization Algorithm","authors":"Ritwik Raha, Arpan Sengupta, Supriya Dhabal","doi":"10.1109/ICCE50343.2020.9290504","DOIUrl":"https://doi.org/10.1109/ICCE50343.2020.9290504","url":null,"abstract":"This paper proposes a novel algorithm for the fusion of medical images using a modified Pulse Coupled Neural Network(PCNN) optimized by the Whale Optimization Algorithm(WOA). In this proposed algorithm the two images are passed through the WOA which computes the necessary parameters for the PCNN feature extractor through a multi-criteria fitness function. The features thus extracted are then used to fuse the images. The resultant fused image is judged by evaluating the entropy, Mutual Information (MI), Structural Similarity (SSIM), etc. as well as a specialized performance metric called feature mutual information.","PeriodicalId":421963,"journal":{"name":"2020 IEEE 1st International Conference for Convergence in Engineering (ICCE)","volume":"441 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-09-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129144457","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2020-09-05DOI: 10.1109/ICCE50343.2020.9290711
Shivdeep, Ankur Biswas, Sudip Ghosh, T. Nag, S. Maity, H. Rahaman
Being lossless, Reversible Image Watermarking (RIW) with Difference Expansion (DE) algorithm is crucial for content authentication, especially for high security medical and military images. In DE-RIW, the secret data bit can be embedded into the Least Significant Bit (LSB) of the difference between two neighboring pixels. Very few researchers have worked on High Level Synthesis (HLS) based implementation of its modified algorithm on Field Programmable Gate Array (FPGA) and Programmable System-On-Chip (P-SoC). Here, to get accelerated performance a modified DE-RIW algorithm is proposed along with its VLSI based hardware implementation both on Xilinx FPGA and P-SoC. In the proposed approach, scheduling is done considering resource constraint criteria. Implementation results through simulation up to burning the design on board needs fewer resources (adder, subtractor, multiplier, divider, register, multiplexer, and comparator) as compared with the similar existing architectures in the literature based on RIW.
{"title":"HLS Based Implementation of Modified DE-RIW Algorithm on FPGA and P-SoC","authors":"Shivdeep, Ankur Biswas, Sudip Ghosh, T. Nag, S. Maity, H. Rahaman","doi":"10.1109/ICCE50343.2020.9290711","DOIUrl":"https://doi.org/10.1109/ICCE50343.2020.9290711","url":null,"abstract":"Being lossless, Reversible Image Watermarking (RIW) with Difference Expansion (DE) algorithm is crucial for content authentication, especially for high security medical and military images. In DE-RIW, the secret data bit can be embedded into the Least Significant Bit (LSB) of the difference between two neighboring pixels. Very few researchers have worked on High Level Synthesis (HLS) based implementation of its modified algorithm on Field Programmable Gate Array (FPGA) and Programmable System-On-Chip (P-SoC). Here, to get accelerated performance a modified DE-RIW algorithm is proposed along with its VLSI based hardware implementation both on Xilinx FPGA and P-SoC. In the proposed approach, scheduling is done considering resource constraint criteria. Implementation results through simulation up to burning the design on board needs fewer resources (adder, subtractor, multiplier, divider, register, multiplexer, and comparator) as compared with the similar existing architectures in the literature based on RIW.","PeriodicalId":421963,"journal":{"name":"2020 IEEE 1st International Conference for Convergence in Engineering (ICCE)","volume":"120 4 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-09-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128487354","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2020-09-05DOI: 10.1109/ICCE50343.2020.9290555
S. Bhadra, Sunirmal Khatua, A. Kundu
An automated traffic signal system having optimal waiting time for all vehicles is proposed in this paper. It is observed that vehicles are sometimes waiting in the traffic signals multiple time in a single journey. In this paper our focus is to minimize the multiple waiting for a particular vehicle in a single journey. Two parameters namely Lane Status and Waiting Ratio are considered for selecting the signal at any particular scenario. Lane status is obtained by implementing Erlang-C and Waiting Ratio is calculated based on previous signal facing data and total journey time. It is found that human willingness for work in terms of energy would be affected adversely while waiting in traffic. Minimizing waiting time also effect the human energy that would be beneficial in every aspect.
{"title":"Optimization of Waiting Time in a Traffic Signal: An Automated Approach","authors":"S. Bhadra, Sunirmal Khatua, A. Kundu","doi":"10.1109/ICCE50343.2020.9290555","DOIUrl":"https://doi.org/10.1109/ICCE50343.2020.9290555","url":null,"abstract":"An automated traffic signal system having optimal waiting time for all vehicles is proposed in this paper. It is observed that vehicles are sometimes waiting in the traffic signals multiple time in a single journey. In this paper our focus is to minimize the multiple waiting for a particular vehicle in a single journey. Two parameters namely Lane Status and Waiting Ratio are considered for selecting the signal at any particular scenario. Lane status is obtained by implementing Erlang-C and Waiting Ratio is calculated based on previous signal facing data and total journey time. It is found that human willingness for work in terms of energy would be affected adversely while waiting in traffic. Minimizing waiting time also effect the human energy that would be beneficial in every aspect.","PeriodicalId":421963,"journal":{"name":"2020 IEEE 1st International Conference for Convergence in Engineering (ICCE)","volume":"47 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-09-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"117029884","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2020-09-05DOI: 10.1109/ICCE50343.2020.9290569
Arnab Santra, Abhirup Sinha, Pritilata Saha, A. Das
Player profile evaluation and player selection play a very important role in any sports and cricket is not an exception to that. In any cricket team, all players can be segregated into two main roles, namely: batsmen and bowlers. To win a match, a team has to be comprised of the best performing players and such a scenario demands an evaluation of a player profile for team selection. Our study proposes an approach to predict batsman ranking by evaluation of a batsman’s past profile. We have used a supervised machine learning technique on past data of Indian Premier League matches to produce a ranking algorithm of batsmen of an ongoing season, which can be used to gauge a batsman’s performance, or to compare between different batsmen. The novelty of our approach lies in the consideration of multiple cricketing parameters, instead of only one parameter i.e. total runs scored, to design the algorithm and in the prediction of top batsmen.
{"title":"A Novel Regression based Technique for Batsman Evaluation in the Indian Premier League","authors":"Arnab Santra, Abhirup Sinha, Pritilata Saha, A. Das","doi":"10.1109/ICCE50343.2020.9290569","DOIUrl":"https://doi.org/10.1109/ICCE50343.2020.9290569","url":null,"abstract":"Player profile evaluation and player selection play a very important role in any sports and cricket is not an exception to that. In any cricket team, all players can be segregated into two main roles, namely: batsmen and bowlers. To win a match, a team has to be comprised of the best performing players and such a scenario demands an evaluation of a player profile for team selection. Our study proposes an approach to predict batsman ranking by evaluation of a batsman’s past profile. We have used a supervised machine learning technique on past data of Indian Premier League matches to produce a ranking algorithm of batsmen of an ongoing season, which can be used to gauge a batsman’s performance, or to compare between different batsmen. The novelty of our approach lies in the consideration of multiple cricketing parameters, instead of only one parameter i.e. total runs scored, to design the algorithm and in the prediction of top batsmen.","PeriodicalId":421963,"journal":{"name":"2020 IEEE 1st International Conference for Convergence in Engineering (ICCE)","volume":"11 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-09-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115761657","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2020-09-05DOI: 10.1109/ICCE50343.2020.9290565
Devjyoti Chakraborty, Snehangshu Bhattacharya, Ayush Thakur, A. R. Gosthipaty, Chira Datta
Heart auscultation is a primary and cost-effective form of clinical examination of the patient. Phonocardiogram (PCG) is a high-fidelity recording that captures the heart auscultation sound. PCG signal is used as a diagnostic test for evaluating the status of the heart and it helps in identifying related diseases.Automating this process would lead to a quicker examination of patients, especially in an environment where the doctor (specialist) to patient ratio is low. This research paper delves into an approach for extracting vital features from a Phonocardiogram and then classifying it into normal and abnormal classes using Deep Learning techniques. Our contributions include (a) Using class weights [1] a heavy class imbalance in the provided medical dataset, (b) Data transformation from an auditory perspective to a visual one (Spectrograms), (c) Using Deep Convolutional Neural Networks to extract features from the spectrogram and (d) Using the extracted features to classify the PCG signals in terms of quality (good vs. bad) and abnormality (normal vs. abnormal).The proposed algorithm achieved the overall score of 91.45% (91.86% sensitivity and 91.04% specificity) and 86.57% (89.78% sensitivity and 83.37% specificity) on train and test data respectively.
{"title":"Feature Extraction and Classification of Phonocardiograms using Convolutional Neural Networks","authors":"Devjyoti Chakraborty, Snehangshu Bhattacharya, Ayush Thakur, A. R. Gosthipaty, Chira Datta","doi":"10.1109/ICCE50343.2020.9290565","DOIUrl":"https://doi.org/10.1109/ICCE50343.2020.9290565","url":null,"abstract":"Heart auscultation is a primary and cost-effective form of clinical examination of the patient. Phonocardiogram (PCG) is a high-fidelity recording that captures the heart auscultation sound. PCG signal is used as a diagnostic test for evaluating the status of the heart and it helps in identifying related diseases.Automating this process would lead to a quicker examination of patients, especially in an environment where the doctor (specialist) to patient ratio is low. This research paper delves into an approach for extracting vital features from a Phonocardiogram and then classifying it into normal and abnormal classes using Deep Learning techniques. Our contributions include (a) Using class weights [1] a heavy class imbalance in the provided medical dataset, (b) Data transformation from an auditory perspective to a visual one (Spectrograms), (c) Using Deep Convolutional Neural Networks to extract features from the spectrogram and (d) Using the extracted features to classify the PCG signals in terms of quality (good vs. bad) and abnormality (normal vs. abnormal).The proposed algorithm achieved the overall score of 91.45% (91.86% sensitivity and 91.04% specificity) and 86.57% (89.78% sensitivity and 83.37% specificity) on train and test data respectively.","PeriodicalId":421963,"journal":{"name":"2020 IEEE 1st International Conference for Convergence in Engineering (ICCE)","volume":"61 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-09-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126012144","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2020-09-05DOI: 10.1109/ICCE50343.2020.9290494
Koushik Dutta, P. K. Mishra, D. Guha
A quasi-optical design approach has been proposed to realize a resonant cavity antenna (RCA) for significant improvements in the gain characteristics. The ray-tracing technique of geometrical optics has been successfully used. About 17 dBi boresight gain has been achieved over the 18% impedance bandwidth of the antenna as evident from the experimental data. This approach should find several applications and may be useful to explore other variants of RCA configurations.
{"title":"Quasi-Optical Design Approach for Resonant Cavity Antenna with Improved Characteristics","authors":"Koushik Dutta, P. K. Mishra, D. Guha","doi":"10.1109/ICCE50343.2020.9290494","DOIUrl":"https://doi.org/10.1109/ICCE50343.2020.9290494","url":null,"abstract":"A quasi-optical design approach has been proposed to realize a resonant cavity antenna (RCA) for significant improvements in the gain characteristics. The ray-tracing technique of geometrical optics has been successfully used. About 17 dBi boresight gain has been achieved over the 18% impedance bandwidth of the antenna as evident from the experimental data. This approach should find several applications and may be useful to explore other variants of RCA configurations.","PeriodicalId":421963,"journal":{"name":"2020 IEEE 1st International Conference for Convergence in Engineering (ICCE)","volume":"18 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-09-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127279597","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2020-09-05DOI: 10.1109/ICCE50343.2020.9290744
R. Chakrabarti, Supriya Dhabal
This paper describes an optimal image denoising method with an efficient cascaded filter structure designed using dragonfly algorithm. Though there are several conventional filtering methods used for image denoising, the proposed method shows much improved result in terms of PSNR, IQI and SSIM values keeping the entire image attributes intact. This proposed image denoising technique exhibits its effectiveness not only in the matter of both quantitative and visual aspects of image but also the performance shows accuracy in presence of various types of noise like Gaussian, Salt and Pepper, and Speckle with different variance values. Furthermore, the experimental results with different real images establish the fact that this approach achieves better optimal solution than existing denoising techniques.
{"title":"An Efficient Cascaded Filter Design using Dragonfly Algorithm for Image Noise Reduction","authors":"R. Chakrabarti, Supriya Dhabal","doi":"10.1109/ICCE50343.2020.9290744","DOIUrl":"https://doi.org/10.1109/ICCE50343.2020.9290744","url":null,"abstract":"This paper describes an optimal image denoising method with an efficient cascaded filter structure designed using dragonfly algorithm. Though there are several conventional filtering methods used for image denoising, the proposed method shows much improved result in terms of PSNR, IQI and SSIM values keeping the entire image attributes intact. This proposed image denoising technique exhibits its effectiveness not only in the matter of both quantitative and visual aspects of image but also the performance shows accuracy in presence of various types of noise like Gaussian, Salt and Pepper, and Speckle with different variance values. Furthermore, the experimental results with different real images establish the fact that this approach achieves better optimal solution than existing denoising techniques.","PeriodicalId":421963,"journal":{"name":"2020 IEEE 1st International Conference for Convergence in Engineering (ICCE)","volume":"15 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-09-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124295190","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Cloud computing is one of the important technologies in the field of Information Technology. Many services are available and provided by different service providers using different cloud technology nowadays. The main problem of cloud computing-based technology is load balancing in different cloud servers. It is one of the important issues in the necessary growth of cloud computation. Demand for the new cloud services with a high-speed service is important issue in this current era. There are various algorithms of load balancing which have been already discussed for an efficient allocation of requests through a proper selection of virtual machines in a cloud environment. In this paper, a new distribution technique of the entire incoming requests among the virtual machines has been proposed with an improved dynamic load balancing approach (IDLBA) in the cloud environment. Thus, its simulation is performed using the CloudAnalyst simulator three times with different numbers of tasks of different length. The simulation result is compared with some previously designed load balancing algorithms [1][2] in the cloud environment. Comparative analysis of simulation results establishes the fact that the incoming tasks are distributed dynamically among different available virtual machines which are of different configurations in a different data center in such a way that comparatively better response time and makespan time are achieved.
{"title":"Improved Dynamic Load Balancing Approach in Cloud Computing","authors":"Soumen Swarnakar, Ritik Kumar, Saurabh Krishn, Chandan Banerjee","doi":"10.1109/ICCE50343.2020.9290602","DOIUrl":"https://doi.org/10.1109/ICCE50343.2020.9290602","url":null,"abstract":"Cloud computing is one of the important technologies in the field of Information Technology. Many services are available and provided by different service providers using different cloud technology nowadays. The main problem of cloud computing-based technology is load balancing in different cloud servers. It is one of the important issues in the necessary growth of cloud computation. Demand for the new cloud services with a high-speed service is important issue in this current era. There are various algorithms of load balancing which have been already discussed for an efficient allocation of requests through a proper selection of virtual machines in a cloud environment. In this paper, a new distribution technique of the entire incoming requests among the virtual machines has been proposed with an improved dynamic load balancing approach (IDLBA) in the cloud environment. Thus, its simulation is performed using the CloudAnalyst simulator three times with different numbers of tasks of different length. The simulation result is compared with some previously designed load balancing algorithms [1][2] in the cloud environment. Comparative analysis of simulation results establishes the fact that the incoming tasks are distributed dynamically among different available virtual machines which are of different configurations in a different data center in such a way that comparatively better response time and makespan time are achieved.","PeriodicalId":421963,"journal":{"name":"2020 IEEE 1st International Conference for Convergence in Engineering (ICCE)","volume":"44 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-09-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126462015","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2020-09-05DOI: 10.1109/ICCE50343.2020.9290699
Aditi Bankura, A. Kundu, S. Guha
In this paper, authors have proposed zone based indexing framework to store data into databases and to retrieve relevant web pages from databases. Web pages are gathered from registered website using web crawlers and relevant web pages are accessed from stored web pages for search queries placed by different users. Response of a search query depends on network framework and indexing structure of data. Orientation of web pages in databases plays a major role to provide minimum delay and maximum accuracy in response of a search query. In our approach, keywords in each web page and search query are identified and mapped with configured zones. Then, association of keywords with zones facilitates to identify databases from available databases to store web pages and to fetch relevant URLs of web pages for processing of search queries. Placement of web pages into databases and processing of search queries are performed with identification of zones using zone based indexing framework to provide accuracy. Comparative analysis has been done to exhibit superior performance of proposed approach over existing framework with respect to response time.
{"title":"Zone based Indexing Model for Database Identification in Search Query Processing","authors":"Aditi Bankura, A. Kundu, S. Guha","doi":"10.1109/ICCE50343.2020.9290699","DOIUrl":"https://doi.org/10.1109/ICCE50343.2020.9290699","url":null,"abstract":"In this paper, authors have proposed zone based indexing framework to store data into databases and to retrieve relevant web pages from databases. Web pages are gathered from registered website using web crawlers and relevant web pages are accessed from stored web pages for search queries placed by different users. Response of a search query depends on network framework and indexing structure of data. Orientation of web pages in databases plays a major role to provide minimum delay and maximum accuracy in response of a search query. In our approach, keywords in each web page and search query are identified and mapped with configured zones. Then, association of keywords with zones facilitates to identify databases from available databases to store web pages and to fetch relevant URLs of web pages for processing of search queries. Placement of web pages into databases and processing of search queries are performed with identification of zones using zone based indexing framework to provide accuracy. Comparative analysis has been done to exhibit superior performance of proposed approach over existing framework with respect to response time.","PeriodicalId":421963,"journal":{"name":"2020 IEEE 1st International Conference for Convergence in Engineering (ICCE)","volume":"31 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-09-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131804874","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2020-09-05DOI: 10.1109/ICCE50343.2020.9290724
S. Dasgupta, S. Sadhu
A decoupling controller for multivariable time delay system, using Internal Model Control (IMC) structure has been presented. This proposed controller structure is loosely comparable to the so named "centralized inverted decoupling controller" reported earlier. However, the proposed controller uses the IMC paradigm in an innovative way and differs in detail from the previously reported controller. The proposed structures and corresponding design methods have been described. Performance of the resulting controllers has been illustrated using an industrially important (Distillation Column) highly coupled 2X2 square system having multiple time delays. Closed loop system performances have been analyzed considering tracking, disturbance rejection and robustness with respect to parametric uncertainty. Comparison has been done between this proposed approach and a predecessor approach.
{"title":"Decoupling Controller Design for a Multivariable Time Delay System","authors":"S. Dasgupta, S. Sadhu","doi":"10.1109/ICCE50343.2020.9290724","DOIUrl":"https://doi.org/10.1109/ICCE50343.2020.9290724","url":null,"abstract":"A decoupling controller for multivariable time delay system, using Internal Model Control (IMC) structure has been presented. This proposed controller structure is loosely comparable to the so named \"centralized inverted decoupling controller\" reported earlier. However, the proposed controller uses the IMC paradigm in an innovative way and differs in detail from the previously reported controller. The proposed structures and corresponding design methods have been described. Performance of the resulting controllers has been illustrated using an industrially important (Distillation Column) highly coupled 2X2 square system having multiple time delays. Closed loop system performances have been analyzed considering tracking, disturbance rejection and robustness with respect to parametric uncertainty. Comparison has been done between this proposed approach and a predecessor approach.","PeriodicalId":421963,"journal":{"name":"2020 IEEE 1st International Conference for Convergence in Engineering (ICCE)","volume":"140 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-09-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124621439","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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