Pub Date : 2011-07-20DOI: 10.1109/PACC.2011.5978899
L. Sivakumar, X. Anitha mary
Coal will play as a major fuel source for power production due to its long term availability. Hence it is necessary to develop clean and efficient coal gasification plants also known as greenhouse power plants. One of the main components in green house power plant is gasifier. The mathematical model developed by ALSTOM for gasifier is highly coupled multivariable system with transfer function of the order of 25. Handling such higher order transfer functions for controller design is found to be very difficult. It is necessary to have lower order transfer functions. This paper discusses the applicability of two methods namely Algebraic method and Reduced Order Approximations to get the reduced order transfer functions. The simulation results show that the algebraic method is more suitable than Reduced order approximation.
{"title":"A Low Order Transfer Function Model for MIMO ALSTOM Gasifier","authors":"L. Sivakumar, X. Anitha mary","doi":"10.1109/PACC.2011.5978899","DOIUrl":"https://doi.org/10.1109/PACC.2011.5978899","url":null,"abstract":"Coal will play as a major fuel source for power production due to its long term availability. Hence it is necessary to develop clean and efficient coal gasification plants also known as greenhouse power plants. One of the main components in green house power plant is gasifier. The mathematical model developed by ALSTOM for gasifier is highly coupled multivariable system with transfer function of the order of 25. Handling such higher order transfer functions for controller design is found to be very difficult. It is necessary to have lower order transfer functions. This paper discusses the applicability of two methods namely Algebraic method and Reduced Order Approximations to get the reduced order transfer functions. The simulation results show that the algebraic method is more suitable than Reduced order approximation.","PeriodicalId":403612,"journal":{"name":"2011 International Conference on Process Automation, Control and Computing","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2011-07-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133413847","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 : 2011-07-20DOI: 10.1109/PACC.2011.5979036
M. Murugan, R. Jeyabharath
The integration of neural networks and fuzzy inference system could be formatted into three main categories: cooperative, concurrent and integrated neuro-fuzzy models namely fuzzy associative memories fuzzy rules extraction using self-organizing maps and systems capable of learning fuzzy set parameters. Mamdani and Takagi-Sugeno type integrated neuro-fuzzy systems were further introduced with a focus on some of the salient features and advantages of the different types of integrated neuro-fuzzy models that have been evolved during last decade. This work focus on the implementation of integrated neuro-fuzzy systems also called hybrid controllers. The Mamdani and Sugeno hybrid controllers are incorporated along with direct torque control to generate more accurate voltage space vectors. This helps in controlling the torque ripple and reduce its amplitude to a great extend. The detail description is given in the following sections. MATLAB design is done with the help of MATLAB Compilers from Math works and the results prove the better control of SRM with reduced torque and flux ripples.
{"title":"Neuro Fuzzy Controller Based Direct Torque Control for SRM Drive","authors":"M. Murugan, R. Jeyabharath","doi":"10.1109/PACC.2011.5979036","DOIUrl":"https://doi.org/10.1109/PACC.2011.5979036","url":null,"abstract":"The integration of neural networks and fuzzy inference system could be formatted into three main categories: cooperative, concurrent and integrated neuro-fuzzy models namely fuzzy associative memories fuzzy rules extraction using self-organizing maps and systems capable of learning fuzzy set parameters. Mamdani and Takagi-Sugeno type integrated neuro-fuzzy systems were further introduced with a focus on some of the salient features and advantages of the different types of integrated neuro-fuzzy models that have been evolved during last decade. This work focus on the implementation of integrated neuro-fuzzy systems also called hybrid controllers. The Mamdani and Sugeno hybrid controllers are incorporated along with direct torque control to generate more accurate voltage space vectors. This helps in controlling the torque ripple and reduce its amplitude to a great extend. The detail description is given in the following sections. MATLAB design is done with the help of MATLAB Compilers from Math works and the results prove the better control of SRM with reduced torque and flux ripples.","PeriodicalId":403612,"journal":{"name":"2011 International Conference on Process Automation, Control and Computing","volume":"62 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2011-07-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133146057","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}
Software quality is the measure of appropriateness of the design of the software and how well it adheres to that design. There are some metrics and measurements to determine the software quality. Software quality measurement is possible only by quantifying the characteristics affecting the software quality. For measuring the quality, the parameters or quality factors are considered that vary over a domain of discourse. The quality factors stated in ISO/IEC 9126 model are used in this paper. Due to the unpredictable nature of these factors or attributes fuzzy approach has been used to estimate the software quality.
{"title":"Quantification of Software Quality Parameters Using Fuzzy Multi Criteria Approach","authors":"Jagat Sesh Challa, Arindam Paul, Yogesh Dada, V. Nerella, Praveen Ranjan Srivastava","doi":"10.1109/PACC.2011.5978957","DOIUrl":"https://doi.org/10.1109/PACC.2011.5978957","url":null,"abstract":"Software quality is the measure of appropriateness of the design of the software and how well it adheres to that design. There are some metrics and measurements to determine the software quality. Software quality measurement is possible only by quantifying the characteristics affecting the software quality. For measuring the quality, the parameters or quality factors are considered that vary over a domain of discourse. The quality factors stated in ISO/IEC 9126 model are used in this paper. Due to the unpredictable nature of these factors or attributes fuzzy approach has been used to estimate the software quality.","PeriodicalId":403612,"journal":{"name":"2011 International Conference on Process Automation, Control and Computing","volume":"20 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2011-07-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124112483","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 : 2011-07-20DOI: 10.1109/PACC.2011.5978933
S. Periyanayagi, V. Sumathy, Ramya Kulandaivel
Abstract - Jamming can interrupt wireless transmission and occur by mistake in form of interference, noise or as collision at the receiver or in the circumstance of an attack. In this paper, we propose a swarm based defense technique for jamming attacks in wireless sensor networks. Swarm intelligence algorithm is proficient enough to adapt change in network topology and traffic. The sender and receiver change channels in order to stay away from the jammer, in channel hoping technique. The jammers remain on a single channel, hoping to disrupt any fragment that may be transmitted in the pulse jamming technique. Using the swarm intelligence technique, the forward ants either unicast or broadcast at each node depending on the availability of the channel information for end of the channel. If the channel information is available, the ants randomly choose the next hop. As the backward ants reaches the source, the data collected is verified which channel there is prevalence of attacker long time, and those are omitted. Simultaneously the forward ants are sent through other channels which are not detected before for attacks. This scheme helps limit the channel maintenance overhead. By simulation results, it is clear that this swarm based defense technique for jamming attack is most effective.
{"title":"A Defense Technique for Jamming Attacks in Wireless Sensor Networks Based on SI","authors":"S. Periyanayagi, V. Sumathy, Ramya Kulandaivel","doi":"10.1109/PACC.2011.5978933","DOIUrl":"https://doi.org/10.1109/PACC.2011.5978933","url":null,"abstract":"Abstract - Jamming can interrupt wireless transmission and occur by mistake in form of interference, noise or as collision at the receiver or in the circumstance of an attack. In this paper, we propose a swarm based defense technique for jamming attacks in wireless sensor networks. Swarm intelligence algorithm is proficient enough to adapt change in network topology and traffic. The sender and receiver change channels in order to stay away from the jammer, in channel hoping technique. The jammers remain on a single channel, hoping to disrupt any fragment that may be transmitted in the pulse jamming technique. Using the swarm intelligence technique, the forward ants either unicast or broadcast at each node depending on the availability of the channel information for end of the channel. If the channel information is available, the ants randomly choose the next hop. As the backward ants reaches the source, the data collected is verified which channel there is prevalence of attacker long time, and those are omitted. Simultaneously the forward ants are sent through other channels which are not detected before for attacks. This scheme helps limit the channel maintenance overhead. By simulation results, it is clear that this swarm based defense technique for jamming attack is most effective.","PeriodicalId":403612,"journal":{"name":"2011 International Conference on Process Automation, Control and Computing","volume":"66 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2011-07-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114490177","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 : 2011-07-20DOI: 10.1109/PACC.2011.5979033
S. Deepa, S. Venkatesan
A simulator in order to calculate the rate of the reaction in the methanol oxidation to formaldehyde process is presented in this paper. Here the Radial Basis Function Network is used to model the process. To choose an optimum number of hidden neuron we use an algorithm called Minimal Resource allocation Network. It recruits hidden neuron based on the novelty of the input data. The training data were obtained from a model available in literature. The network is trained with the literature data and the resulted model gives a good prediction of rate of reaction of formaldehyde formation.
{"title":"A Novel Simulator Using Minimal Resource Allocation Network and Its Application in Industrial Methanol Oxidation to Formaldehyde","authors":"S. Deepa, S. Venkatesan","doi":"10.1109/PACC.2011.5979033","DOIUrl":"https://doi.org/10.1109/PACC.2011.5979033","url":null,"abstract":"A simulator in order to calculate the rate of the reaction in the methanol oxidation to formaldehyde process is presented in this paper. Here the Radial Basis Function Network is used to model the process. To choose an optimum number of hidden neuron we use an algorithm called Minimal Resource allocation Network. It recruits hidden neuron based on the novelty of the input data. The training data were obtained from a model available in literature. The network is trained with the literature data and the resulted model gives a good prediction of rate of reaction of formaldehyde formation.","PeriodicalId":403612,"journal":{"name":"2011 International Conference on Process Automation, Control and Computing","volume":"228 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2011-07-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114748528","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 : 2011-07-20DOI: 10.1109/PACC.2011.5978857
Tamal Saha, S. Mahapatra
A wireless sensor network consists of a number of sensor nodes connected by links. In wireless sensor networks, some sensor nodes may be faulty due to having faulty sensors or intermittently faulty processing logic units. A system level distributed fault diagnosis algorithm is proposed to diagnose a node and the type of fault of the faulty node. The proposed algorithm is simulated assuming 128 sensor nodes interconnected to form an arbitrary network topology using ns-2.
{"title":"Distributed Fault Diagnosis in Wireless Sensor Networks","authors":"Tamal Saha, S. Mahapatra","doi":"10.1109/PACC.2011.5978857","DOIUrl":"https://doi.org/10.1109/PACC.2011.5978857","url":null,"abstract":"A wireless sensor network consists of a number of sensor nodes connected by links. In wireless sensor networks, some sensor nodes may be faulty due to having faulty sensors or intermittently faulty processing logic units. A system level distributed fault diagnosis algorithm is proposed to diagnose a node and the type of fault of the faulty node. The proposed algorithm is simulated assuming 128 sensor nodes interconnected to form an arbitrary network topology using ns-2.","PeriodicalId":403612,"journal":{"name":"2011 International Conference on Process Automation, Control and Computing","volume":"40 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2011-07-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114388266","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 : 2011-07-20DOI: 10.1109/PACC.2011.5979001
Y. Dhayaneswaran, K. Vishnu Murthy, R. Balamurugan
The increasing amounts of three-phase squirrel-cage induction motors over the years are fed by variable-speed drives. In such a machine high frequency generation is caused by the high carrier frequencies of the pulse-width modulation, the associated short rise times of the IGBT output, and the reflected waves from the motor terminals. EMI is also produced by the harmonics which are generated by the carrier frequencies. This EMI/RFI is also referred to as electrical noise. This paper is focused on the influence of the electrical noise emitted by variable-speed drives on field components in Textile machines and CNC Lathe machines. Components failed during a year have been collected and possible solutions have been proposed.
{"title":"Review on Influence of Electrical Noise on Field Elements","authors":"Y. Dhayaneswaran, K. Vishnu Murthy, R. Balamurugan","doi":"10.1109/PACC.2011.5979001","DOIUrl":"https://doi.org/10.1109/PACC.2011.5979001","url":null,"abstract":"The increasing amounts of three-phase squirrel-cage induction motors over the years are fed by variable-speed drives. In such a machine high frequency generation is caused by the high carrier frequencies of the pulse-width modulation, the associated short rise times of the IGBT output, and the reflected waves from the motor terminals. EMI is also produced by the harmonics which are generated by the carrier frequencies. This EMI/RFI is also referred to as electrical noise. This paper is focused on the influence of the electrical noise emitted by variable-speed drives on field components in Textile machines and CNC Lathe machines. Components failed during a year have been collected and possible solutions have been proposed.","PeriodicalId":403612,"journal":{"name":"2011 International Conference on Process Automation, Control and Computing","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2011-07-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116027698","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 : 2011-07-20DOI: 10.1109/PACC.2011.5978861
B. K. Roy, K. Santhosh
In this paper, we propose a scheme to increase the linearity range of the capacitance level sensor (CLS) and make independent of the permittivity of the liquid used. The capacitance from the CLS is first converted to frequency by a timer circuit and then frequency is converted to voltage by a frequency to voltage converter. The relation is nonlinear and depends on permittivity of liquid. Artificial Neural network (ANN) model is used in cascade with the frequency to voltage converter. This arrangement has the effect of linear relation between level to be measured and the output of the ANN model. Further this is independent of permittivity of liquid used. The proposed ANN-based scheme incorporates intelligence into the sensor. Using Matlab environment the training has been done to design a model of ANN.
{"title":"An Intelligent Instrument for Measuring Liquid Level","authors":"B. K. Roy, K. Santhosh","doi":"10.1109/PACC.2011.5978861","DOIUrl":"https://doi.org/10.1109/PACC.2011.5978861","url":null,"abstract":"In this paper, we propose a scheme to increase the linearity range of the capacitance level sensor (CLS) and make independent of the permittivity of the liquid used. The capacitance from the CLS is first converted to frequency by a timer circuit and then frequency is converted to voltage by a frequency to voltage converter. The relation is nonlinear and depends on permittivity of liquid. Artificial Neural network (ANN) model is used in cascade with the frequency to voltage converter. This arrangement has the effect of linear relation between level to be measured and the output of the ANN model. Further this is independent of permittivity of liquid used. The proposed ANN-based scheme incorporates intelligence into the sensor. Using Matlab environment the training has been done to design a model of ANN.","PeriodicalId":403612,"journal":{"name":"2011 International Conference on Process Automation, Control and Computing","volume":"35 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2011-07-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132404389","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 : 2011-07-20DOI: 10.1109/PACC.2011.5978959
D. Prince Winston, M. Saravanan, S. Arockia Edwin Xavier
Due to robustness, reliability, low price and maintenance free operation, induction motors are used in most of the industrial applications. The need for energy conservation is increasing nowadays due to continuous increase in energy demand. The influence of these motors in energy intensive industries is significant in total operational cost. This paper describes a new energy conservation scheme for three phase induction motor with the help of neural network. In this new energy conservation scheme voltage compensation was employed for the various load conditions. Here neural network is used to control the voltage level for the various load conditions. Matlab simulation is done for 5 Hp, 400V, 50Hz and 7.3A three phase squirrel cage induction motor employing the new energy conservation scheme with the help of neural network.
{"title":"Neural Network Based New Energy Conservation Scheme for Three Phase Induction Motor Operating under Varying Load Torques","authors":"D. Prince Winston, M. Saravanan, S. Arockia Edwin Xavier","doi":"10.1109/PACC.2011.5978959","DOIUrl":"https://doi.org/10.1109/PACC.2011.5978959","url":null,"abstract":"Due to robustness, reliability, low price and maintenance free operation, induction motors are used in most of the industrial applications. The need for energy conservation is increasing nowadays due to continuous increase in energy demand. The influence of these motors in energy intensive industries is significant in total operational cost. This paper describes a new energy conservation scheme for three phase induction motor with the help of neural network. In this new energy conservation scheme voltage compensation was employed for the various load conditions. Here neural network is used to control the voltage level for the various load conditions. Matlab simulation is done for 5 Hp, 400V, 50Hz and 7.3A three phase squirrel cage induction motor employing the new energy conservation scheme with the help of neural network.","PeriodicalId":403612,"journal":{"name":"2011 International Conference on Process Automation, Control and Computing","volume":"56 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2011-07-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131979971","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 : 2011-07-20DOI: 10.1109/PACC.2011.5978983
S. Vijayalakshmi, V. Mohan, M. S. Sassirekha, O. R. Deepika
Abstract-Finding Frequent Sequential Pattern (FSP) is an important problem in web usage mining. In this paper, we systematically explore a pattern-growth approach for efficient mining of sequential patterns in large sequence database. The approaches adopts a (divide and conquer) pattern-growth principle as follows: Sequence databases are recursively projected into a set of smaller projected databases based on the current sequential pattern(s), and sequential patterns are grown in each projected databases by exploring only locally frequent fragments. Our proposed method combines tree projection and prefix growth features from pattern-growth category with position coded feature from early-pruning category, all of these features are key characteristics of their respective categories, so we consider our proposed method as a pattern growth / early-pruning hybrid algorithm that considerably reduces execution time. These approaches were implemented in hybrid concrete method using algorithms of sequential pattern mining.
{"title":"Extracting Sequential Access Pattern from Pre-Processed Web Logs","authors":"S. Vijayalakshmi, V. Mohan, M. S. Sassirekha, O. R. Deepika","doi":"10.1109/PACC.2011.5978983","DOIUrl":"https://doi.org/10.1109/PACC.2011.5978983","url":null,"abstract":"Abstract-Finding Frequent Sequential Pattern (FSP) is an important problem in web usage mining. In this paper, we systematically explore a pattern-growth approach for efficient mining of sequential patterns in large sequence database. The approaches adopts a (divide and conquer) pattern-growth principle as follows: Sequence databases are recursively projected into a set of smaller projected databases based on the current sequential pattern(s), and sequential patterns are grown in each projected databases by exploring only locally frequent fragments. Our proposed method combines tree projection and prefix growth features from pattern-growth category with position coded feature from early-pruning category, all of these features are key characteristics of their respective categories, so we consider our proposed method as a pattern growth / early-pruning hybrid algorithm that considerably reduces execution time. These approaches were implemented in hybrid concrete method using algorithms of sequential pattern mining.","PeriodicalId":403612,"journal":{"name":"2011 International Conference on Process Automation, Control and Computing","volume":"87 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2011-07-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132173941","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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