Pub Date : 2000-01-19DOI: 10.1109/ICIT.2000.854235
V. Sharma, B. Singh, S. Murthy
This paper presents a simple analog control scheme for speed control of switched reluctance motor (SRM). It is designed to operate with minimum number of switching devices. It makes use of rotor position signals, speed signal, and current signals in the closed loop feedback control. The proposed scheme is useful for low power rating applications. Use of off-the-shelf electronic components makes the controller simple, reliable, and economical. The test results are presented for 4 kW, 4-phase, 1500 rpm motor which has 8 poles on the stator and 6 poles on the rotor.
{"title":"Development of a simple analog controller for switched reluctance motor","authors":"V. Sharma, B. Singh, S. Murthy","doi":"10.1109/ICIT.2000.854235","DOIUrl":"https://doi.org/10.1109/ICIT.2000.854235","url":null,"abstract":"This paper presents a simple analog control scheme for speed control of switched reluctance motor (SRM). It is designed to operate with minimum number of switching devices. It makes use of rotor position signals, speed signal, and current signals in the closed loop feedback control. The proposed scheme is useful for low power rating applications. Use of off-the-shelf electronic components makes the controller simple, reliable, and economical. The test results are presented for 4 kW, 4-phase, 1500 rpm motor which has 8 poles on the stator and 6 poles on the rotor.","PeriodicalId":405648,"journal":{"name":"Proceedings of IEEE International Conference on Industrial Technology 2000 (IEEE Cat. No.00TH8482)","volume":"27 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2000-01-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121207435","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 : 2000-01-19DOI: 10.1109/ICIT.2000.854246
Amit Kumar Srivastava, S. K. Srivastava, K. Shukla
A neural classifier has been designed by a new two-phase hybrid training algorithm introduced by us for classification of hazardous vapours. The neural network is trained using genetic algorithm in initial phase. This is followed by a second phase of backpropagation training that uses weight matrix determined by first phase for initialization. For establishing the superior performance of our classifier, published data from polymer-coated surface-acoustic wave (SAW) sensors array exposed to varying concentration of each of nine vapours belonging to two different classes have been used. Vapours of class I are toxic vapours of interest in ambient air that contains common interferents (class II vapours) at much higher concentration. Performance of the classifier is evaluated by reducing dimensionality of resulting data matrix from 4 to 1 by taking a different set of sensors. We show that as the dimension is reduced, the gas identification problem becomes harder for backpropagation. Whereas the same set of problems when solved using a genetic algorithm with heuristic switch over to backpropagation as a training paradigm, significantly better results are obtained in predicting class and type of test vapours.
{"title":"On the performance evaluation of hybrid-trained neural classifier for the detection of hazardous vapours using responses from SAW sensors array","authors":"Amit Kumar Srivastava, S. K. Srivastava, K. Shukla","doi":"10.1109/ICIT.2000.854246","DOIUrl":"https://doi.org/10.1109/ICIT.2000.854246","url":null,"abstract":"A neural classifier has been designed by a new two-phase hybrid training algorithm introduced by us for classification of hazardous vapours. The neural network is trained using genetic algorithm in initial phase. This is followed by a second phase of backpropagation training that uses weight matrix determined by first phase for initialization. For establishing the superior performance of our classifier, published data from polymer-coated surface-acoustic wave (SAW) sensors array exposed to varying concentration of each of nine vapours belonging to two different classes have been used. Vapours of class I are toxic vapours of interest in ambient air that contains common interferents (class II vapours) at much higher concentration. Performance of the classifier is evaluated by reducing dimensionality of resulting data matrix from 4 to 1 by taking a different set of sensors. We show that as the dimension is reduced, the gas identification problem becomes harder for backpropagation. Whereas the same set of problems when solved using a genetic algorithm with heuristic switch over to backpropagation as a training paradigm, significantly better results are obtained in predicting class and type of test vapours.","PeriodicalId":405648,"journal":{"name":"Proceedings of IEEE International Conference on Industrial Technology 2000 (IEEE Cat. No.00TH8482)","volume":"9 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2000-01-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126934995","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 : 2000-01-19DOI: 10.1109/ICIT.2000.854119
B. Chaudhari, S. Wekhande, S. Dambhare, S. S. Dhamse
Emerging high-volume low-power variable speed AC motor drives have the stringent requirements of low cost and compactness. Most low-power, low-performance applications use two-phase induction motors. A new control scheme is proposed for a two-phase inverter to control a two-phase induction motor in this paper. The proposed scheme is simple, cost-effective and reduces inverter switching losses significantly as four out of six switches operate on fundamental frequency. The objective of the work is to provide cost effective inverter which can induce a change from constant speed to variable speed operation in the low-power range.
{"title":"New energy efficient drive for 2 phase induction motor with minimum switching losses","authors":"B. Chaudhari, S. Wekhande, S. Dambhare, S. S. Dhamse","doi":"10.1109/ICIT.2000.854119","DOIUrl":"https://doi.org/10.1109/ICIT.2000.854119","url":null,"abstract":"Emerging high-volume low-power variable speed AC motor drives have the stringent requirements of low cost and compactness. Most low-power, low-performance applications use two-phase induction motors. A new control scheme is proposed for a two-phase inverter to control a two-phase induction motor in this paper. The proposed scheme is simple, cost-effective and reduces inverter switching losses significantly as four out of six switches operate on fundamental frequency. The objective of the work is to provide cost effective inverter which can induce a change from constant speed to variable speed operation in the low-power range.","PeriodicalId":405648,"journal":{"name":"Proceedings of IEEE International Conference on Industrial Technology 2000 (IEEE Cat. No.00TH8482)","volume":"60 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2000-01-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127309199","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 : 2000-01-19DOI: 10.1109/ICIT.2000.854256
K. Tang, K. Man, R. Istepanian
Hierarchical genetic algorithm (HGA) is formulated to design the H/sub /spl infin// controller for the teleoperation system used in microsurgery. Such a HGA is capable of searching the structure of the H/sub /spl infin// and its coefficients simultaneously. A multiple objective ranking scheme is also incorporated so that both the force and position transparency are optimized against any strictly passive environment.
{"title":"Teleoperation controller design using hierarchical genetic algorithm","authors":"K. Tang, K. Man, R. Istepanian","doi":"10.1109/ICIT.2000.854256","DOIUrl":"https://doi.org/10.1109/ICIT.2000.854256","url":null,"abstract":"Hierarchical genetic algorithm (HGA) is formulated to design the H/sub /spl infin// controller for the teleoperation system used in microsurgery. Such a HGA is capable of searching the structure of the H/sub /spl infin// and its coefficients simultaneously. A multiple objective ranking scheme is also incorporated so that both the force and position transparency are optimized against any strictly passive environment.","PeriodicalId":405648,"journal":{"name":"Proceedings of IEEE International Conference on Industrial Technology 2000 (IEEE Cat. No.00TH8482)","volume":"12 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2000-01-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"117037797","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 : 2000-01-19DOI: 10.1109/ICIT.2000.854157
L. Horváth, J. K. Tar, I. Rudas, H. Shamsudin
The main essence of the paper is an introduction of an application of Petri net model entity representations in concurrent engineering processes. Characteristics of the proposed modeling include feature based and multiple leveled model structure, generic model entities and integrated modeling approach. The authors have developed a manufacturing process modeling approach and methodology that is suitable for continuous modification of part manufacturing processes on the basis of messages about changes of part models and other conditions. Generic manufacturing models involve variants. Entities in the model are represented by Petri nets that can be repeatedly executed for changed conditions. The method assumes a reorderable form feature based part model. The paper is organized as follows. Firstly the related and actual issues of concurrent engineering and their relations process modeling are outlined. Following this, the proposed approach and the methodology of integration feature based part models with part manufacturing models are explained. Next application of the proposed integrated modeling in concurrent engineering processes is detailed. Finally, possible benefits of the proposed model in present day modeling are concluded.
{"title":"Generic modeling of manufacturing processes using Petri nets for concurrent engineering","authors":"L. Horváth, J. K. Tar, I. Rudas, H. Shamsudin","doi":"10.1109/ICIT.2000.854157","DOIUrl":"https://doi.org/10.1109/ICIT.2000.854157","url":null,"abstract":"The main essence of the paper is an introduction of an application of Petri net model entity representations in concurrent engineering processes. Characteristics of the proposed modeling include feature based and multiple leveled model structure, generic model entities and integrated modeling approach. The authors have developed a manufacturing process modeling approach and methodology that is suitable for continuous modification of part manufacturing processes on the basis of messages about changes of part models and other conditions. Generic manufacturing models involve variants. Entities in the model are represented by Petri nets that can be repeatedly executed for changed conditions. The method assumes a reorderable form feature based part model. The paper is organized as follows. Firstly the related and actual issues of concurrent engineering and their relations process modeling are outlined. Following this, the proposed approach and the methodology of integration feature based part models with part manufacturing models are explained. Next application of the proposed integrated modeling in concurrent engineering processes is detailed. Finally, possible benefits of the proposed model in present day modeling are concluded.","PeriodicalId":405648,"journal":{"name":"Proceedings of IEEE International Conference on Industrial Technology 2000 (IEEE Cat. No.00TH8482)","volume":"18 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2000-01-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131935072","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 : 2000-01-19DOI: 10.1109/ICIT.2000.854091
A. Tripathi, S.P. Das
In this paper the direct torque and flux control method for control of speed and torque of a three phase induction motor has been proposed using a PC-based real time control algorithm. This type of an industrial drive can have two distinct advantages: (i) enhanced flexibility i.e. only a high speed data-acquisition card and the real time control software are needed to retrofit another drive having similar hardware components; and (ii) only the inverter circuit needs to be fabricated, the switching status of which is provided by the control software.
{"title":"A PC-based hardware and software design for a direct torque and flux controlled induction motor drive system","authors":"A. Tripathi, S.P. Das","doi":"10.1109/ICIT.2000.854091","DOIUrl":"https://doi.org/10.1109/ICIT.2000.854091","url":null,"abstract":"In this paper the direct torque and flux control method for control of speed and torque of a three phase induction motor has been proposed using a PC-based real time control algorithm. This type of an industrial drive can have two distinct advantages: (i) enhanced flexibility i.e. only a high speed data-acquisition card and the real time control software are needed to retrofit another drive having similar hardware components; and (ii) only the inverter circuit needs to be fabricated, the switching status of which is provided by the control software.","PeriodicalId":405648,"journal":{"name":"Proceedings of IEEE International Conference on Industrial Technology 2000 (IEEE Cat. No.00TH8482)","volume":"22 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2000-01-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134308963","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 : 2000-01-19DOI: 10.1109/ICIT.2000.854097
R. Chatterjee, F. Matsuno
The present work explores a simple off-line method to extract the intuitive actions used by humans to avoid obstacles during motion in unknown environments. The proposed method analyzes the hand drawn trajectories by human individuals on environment maps showing typical obstacle placements, and evaluates the navigational decision parameters. The translation and steering velocity variation along the curve are computed based on the constraints of the mobile entity (e.g., an autonomous mobile robot). The decisions are considered to be taken in the context of the distances of the obstacles around the current point on the trajectory. The instances of environmental situations and corresponding intended actions are used to train a neural network. To reduce the complexity of the network, the number of input variables for the network is reduced by considering only single sided reflex behaviors. The left-right symmetry of the perception-action behaviors allows the single sided reflex network to be used for both left and right hand side reflex in the vicinity of obstacles. Simulation results are presented to show the effectiveness of the proposed strategy in typical obstacle situations.
{"title":"Learning obstacle avoidance reflex behavior for autonomous navigation from hand-drawn trajectories","authors":"R. Chatterjee, F. Matsuno","doi":"10.1109/ICIT.2000.854097","DOIUrl":"https://doi.org/10.1109/ICIT.2000.854097","url":null,"abstract":"The present work explores a simple off-line method to extract the intuitive actions used by humans to avoid obstacles during motion in unknown environments. The proposed method analyzes the hand drawn trajectories by human individuals on environment maps showing typical obstacle placements, and evaluates the navigational decision parameters. The translation and steering velocity variation along the curve are computed based on the constraints of the mobile entity (e.g., an autonomous mobile robot). The decisions are considered to be taken in the context of the distances of the obstacles around the current point on the trajectory. The instances of environmental situations and corresponding intended actions are used to train a neural network. To reduce the complexity of the network, the number of input variables for the network is reduced by considering only single sided reflex behaviors. The left-right symmetry of the perception-action behaviors allows the single sided reflex network to be used for both left and right hand side reflex in the vicinity of obstacles. Simulation results are presented to show the effectiveness of the proposed strategy in typical obstacle situations.","PeriodicalId":405648,"journal":{"name":"Proceedings of IEEE International Conference on Industrial Technology 2000 (IEEE Cat. No.00TH8482)","volume":"31 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2000-01-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133984501","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 : 2000-01-19DOI: 10.1109/ICIT.2000.854248
K. Hans Raj, R.S. Sharma, S. Srivastava, C. Patvardhan
This paper presents a new single-objective neuro-stochastic search technique (SONSST) for the economic load estimation problem in hot extrusion which is often used to produce long straight metal products of constant cross-sections such as bars, solid and hollow sections, tubes, wires and strips from materials that cannot be formed by cold extrusion. The shape of the dies and the temperature developed during extrusion and the velocity of the dies significantly influence forging force at which the process is to be carried out. In order to understand the complex relationship between the material and process variables, a few finite element models are developed and simulated in the FORGE2 environment. These finite element simulations are used to train a neural network (NN) model. Later the same model is incorporated along with a genetic algorithm (GA) and simulated annealing (SA) to form SONSST. It incorporates a genetic crossover operator BLX-/spl alpha/ and a problem specific mutation operator incorporating a local search heuristic: to provide it a better search capability. Extensive simulations have been carried out considering various aspects and the results are validated with those of the existing finite element method in the literature. These results indicate that the new SONSST heuristic converges to better solutions rapidly. SONSST is a truly single-objective technique as it provides the values of various process parameters for optimizing single objective (extrusion load), in a single run and thus assists in achieving energy and material saving, quality improvement and in the development of sound extruded parts.
{"title":"Optimization of hot extrusion using single objective neuro stochastic search technique","authors":"K. Hans Raj, R.S. Sharma, S. Srivastava, C. Patvardhan","doi":"10.1109/ICIT.2000.854248","DOIUrl":"https://doi.org/10.1109/ICIT.2000.854248","url":null,"abstract":"This paper presents a new single-objective neuro-stochastic search technique (SONSST) for the economic load estimation problem in hot extrusion which is often used to produce long straight metal products of constant cross-sections such as bars, solid and hollow sections, tubes, wires and strips from materials that cannot be formed by cold extrusion. The shape of the dies and the temperature developed during extrusion and the velocity of the dies significantly influence forging force at which the process is to be carried out. In order to understand the complex relationship between the material and process variables, a few finite element models are developed and simulated in the FORGE2 environment. These finite element simulations are used to train a neural network (NN) model. Later the same model is incorporated along with a genetic algorithm (GA) and simulated annealing (SA) to form SONSST. It incorporates a genetic crossover operator BLX-/spl alpha/ and a problem specific mutation operator incorporating a local search heuristic: to provide it a better search capability. Extensive simulations have been carried out considering various aspects and the results are validated with those of the existing finite element method in the literature. These results indicate that the new SONSST heuristic converges to better solutions rapidly. SONSST is a truly single-objective technique as it provides the values of various process parameters for optimizing single objective (extrusion load), in a single run and thus assists in achieving energy and material saving, quality improvement and in the development of sound extruded parts.","PeriodicalId":405648,"journal":{"name":"Proceedings of IEEE International Conference on Industrial Technology 2000 (IEEE Cat. No.00TH8482)","volume":"5 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2000-01-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129200108","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 : 2000-01-19DOI: 10.1109/ICIT.2000.854251
S. Chowdhuri, A. Mukherjee
The conventional controllers used for DC machines are static and their parameters are fixed through proper design. The classical approach is to use a PID controller with constant parameters after analyzing the stability criterion. The modern approach is to use controllers based on fuzzy logic or other AI techniques. The authors have chosen a speed-tracking problem where a DC machine has to follow a time varying speed demand. The controller coefficients are fixed through an evolutionary algorithm. Representative values of steady state error, maximum overshoot and transient rise time are computed through feature extraction algorithms. Now, the fitness of each member is computed as a fuzzy value based on some predefined fuzzy functions involving the feature values. This fuzzy fitness value governs the selection of coefficients through a genetic algorithm until convergence is obtained. The performance has been studied with various fitness functions and the results are found to be satisfactory.
{"title":"An evolutionary approach to optimize speed controller of DC machines","authors":"S. Chowdhuri, A. Mukherjee","doi":"10.1109/ICIT.2000.854251","DOIUrl":"https://doi.org/10.1109/ICIT.2000.854251","url":null,"abstract":"The conventional controllers used for DC machines are static and their parameters are fixed through proper design. The classical approach is to use a PID controller with constant parameters after analyzing the stability criterion. The modern approach is to use controllers based on fuzzy logic or other AI techniques. The authors have chosen a speed-tracking problem where a DC machine has to follow a time varying speed demand. The controller coefficients are fixed through an evolutionary algorithm. Representative values of steady state error, maximum overshoot and transient rise time are computed through feature extraction algorithms. Now, the fitness of each member is computed as a fuzzy value based on some predefined fuzzy functions involving the feature values. This fuzzy fitness value governs the selection of coefficients through a genetic algorithm until convergence is obtained. The performance has been studied with various fitness functions and the results are found to be satisfactory.","PeriodicalId":405648,"journal":{"name":"Proceedings of IEEE International Conference on Industrial Technology 2000 (IEEE Cat. No.00TH8482)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2000-01-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128459029","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 : 2000-01-19DOI: 10.1109/ICIT.2000.854244
C. Su, Guor-Rurng Lii, Jiann-Jung Chen
This research proposes a new method for long-term generation expansion planning. The method adopts a multi-aspect optimal approach which considers the capital cost of the newly added units, the maintenance and fuel costs, environmental impact, reliability, etc. To accommodate the growth of power load, the generation capacity needs to expand to meet the load demand. In order to find an optimal alternative to increase the generation capacity and satisfy different constraints economically and efficiently, the optimization technique is employed. The dynamic programming (DP) as the optimization method is used in this study. Since the requirements of environmental standard and power quality are getting more and more strict, economical factors are no more the unique one to weigh for the generation expansion planning. The environmental protection and reliability are also important factors of the problem. However, types of pollution are very complicated and are not easy to incorporate into the solution model. In this research, we apply the fuzzy theory to represent the state of pollution and judge if a combination of investment is acceptable or not. Moreover by employing the fuzzy technique, we can delete a lot of unnecessary paths and states to reduce the computation burden of DP. Finally we use an example to illustrate and prove the applicability and validity of the presented approach.
{"title":"Long-term generation expansion planning employing dynamic programming and fuzzy techniques","authors":"C. Su, Guor-Rurng Lii, Jiann-Jung Chen","doi":"10.1109/ICIT.2000.854244","DOIUrl":"https://doi.org/10.1109/ICIT.2000.854244","url":null,"abstract":"This research proposes a new method for long-term generation expansion planning. The method adopts a multi-aspect optimal approach which considers the capital cost of the newly added units, the maintenance and fuel costs, environmental impact, reliability, etc. To accommodate the growth of power load, the generation capacity needs to expand to meet the load demand. In order to find an optimal alternative to increase the generation capacity and satisfy different constraints economically and efficiently, the optimization technique is employed. The dynamic programming (DP) as the optimization method is used in this study. Since the requirements of environmental standard and power quality are getting more and more strict, economical factors are no more the unique one to weigh for the generation expansion planning. The environmental protection and reliability are also important factors of the problem. However, types of pollution are very complicated and are not easy to incorporate into the solution model. In this research, we apply the fuzzy theory to represent the state of pollution and judge if a combination of investment is acceptable or not. Moreover by employing the fuzzy technique, we can delete a lot of unnecessary paths and states to reduce the computation burden of DP. Finally we use an example to illustrate and prove the applicability and validity of the presented approach.","PeriodicalId":405648,"journal":{"name":"Proceedings of IEEE International Conference on Industrial Technology 2000 (IEEE Cat. No.00TH8482)","volume":"74 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2000-01-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116018921","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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