Pub Date : 2000-01-19DOI: 10.1109/ICIT.2000.854093
D. Yousfi, M. Azizi, A. Saad
Position and speed estimation algorithms for a synchronous motor are presented in this paper. Its principle is inspired from two existing techniques. The aim is to elaborate an estimator that is able to cancel any initial position error and be robust toward DC disturbance. This latest property is realized by using an improved integrator in the estimation procedure. Simulation and experimental results are presented to show the realization of the objectives.
{"title":"Improved position and speed estimation algorithm for synchronous motor","authors":"D. Yousfi, M. Azizi, A. Saad","doi":"10.1109/ICIT.2000.854093","DOIUrl":"https://doi.org/10.1109/ICIT.2000.854093","url":null,"abstract":"Position and speed estimation algorithms for a synchronous motor are presented in this paper. Its principle is inspired from two existing techniques. The aim is to elaborate an estimator that is able to cancel any initial position error and be robust toward DC disturbance. This latest property is realized by using an improved integrator in the estimation procedure. Simulation and experimental results are presented to show the realization of the objectives.","PeriodicalId":405648,"journal":{"name":"Proceedings of IEEE International Conference on Industrial Technology 2000 (IEEE Cat. No.00TH8482)","volume":"2 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":"129658388","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.2000.854109
A. Kumar, S. Gupta
In this paper we propose a technique for the design and development of an automatic visual inspection system for identification of surface defects produced in the steel industry. The proposed DSP based system is implemented using an interconnection of four subsystems: (i) sensing, (ii) data acquisition, (iii) feature (content) extraction and (iv) feature comparison. The system is based on identification of defects using content-based matching of query image with those of database images. The query image is the on-line grabbed image by CCD cameras. The database (off-line) is prepared for all the expected query image by extracting relevant features. An image histogram is used for feature extraction. The computational complexity and storage requirements are reduced by decomposing histogram using wavelet transform. The root mean square (RMS) metric is used for distance calculation.
{"title":"Real time DSP based identification of surface defects using content-based imaging technique","authors":"A. Kumar, S. Gupta","doi":"10.1109/ICIT.2000.854109","DOIUrl":"https://doi.org/10.1109/ICIT.2000.854109","url":null,"abstract":"In this paper we propose a technique for the design and development of an automatic visual inspection system for identification of surface defects produced in the steel industry. The proposed DSP based system is implemented using an interconnection of four subsystems: (i) sensing, (ii) data acquisition, (iii) feature (content) extraction and (iv) feature comparison. The system is based on identification of defects using content-based matching of query image with those of database images. The query image is the on-line grabbed image by CCD cameras. The database (off-line) is prepared for all the expected query image by extracting relevant features. An image histogram is used for feature extraction. The computational complexity and storage requirements are reduced by decomposing histogram using wavelet transform. The root mean square (RMS) metric is used for distance calculation.","PeriodicalId":405648,"journal":{"name":"Proceedings of IEEE International Conference on Industrial Technology 2000 (IEEE Cat. No.00TH8482)","volume":"64 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":"130929793","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.2000.854264
A. Sahani, S. K. Nagar, J. Pal
An algorithm for designing reduced order digital controller which can replace an existing high order cascade digital controller is presented. The parameters of the reduced order controller are obtained by applying frequency response technique. The new algorithm is illustrated by some examples.
{"title":"An algorithm for reduced order modelling of digital controllers","authors":"A. Sahani, S. K. Nagar, J. Pal","doi":"10.1109/ICIT.2000.854264","DOIUrl":"https://doi.org/10.1109/ICIT.2000.854264","url":null,"abstract":"An algorithm for designing reduced order digital controller which can replace an existing high order cascade digital controller is presented. The parameters of the reduced order controller are obtained by applying frequency response technique. The new algorithm is illustrated by some examples.","PeriodicalId":405648,"journal":{"name":"Proceedings of IEEE International Conference on Industrial Technology 2000 (IEEE Cat. No.00TH8482)","volume":"38 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":"126471845","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.2000.854097
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.2000.854179
A. Fratta, P. Guglielmi, G. Pellegrino, F. Villata
Previous works have shown the power design effectiveness of novel H-bridge-based DC-DC boost conversion structure, as well as the feasibility of real-time DC-link voltage adaptation to inverter load, in battery-supplied AC motor drives. In this paper a novel test bench has been developed, suitable for power loss measurements in high-efficiency bi-directional DC-DC converters. In order to allow for quasi-direct measurement of the lost power, the concept is to operate the converter by input current having constant module, handling alternating energy flow between two large capacitor banks at given input/output DC voltages. Accordingly, the input current reference is a low frequency (65 Hz) rectangular-wave, whose duty-cycle is regulated by suitable voltage loop due to constant module operation. Except for added large capacitor banks' losses and other secondary effects related to 65 Hz operation, the input DC power supply is shown equivalent to conversion losses at given DC working point. The results point-out the high efficiency of the conversion structure well matched with simple analytical models.
{"title":"Power loss analysis and measurement of a high efficiency DC-DC converter for EV traction AC drives","authors":"A. Fratta, P. Guglielmi, G. Pellegrino, F. Villata","doi":"10.1109/ICIT.2000.854179","DOIUrl":"https://doi.org/10.1109/ICIT.2000.854179","url":null,"abstract":"Previous works have shown the power design effectiveness of novel H-bridge-based DC-DC boost conversion structure, as well as the feasibility of real-time DC-link voltage adaptation to inverter load, in battery-supplied AC motor drives. In this paper a novel test bench has been developed, suitable for power loss measurements in high-efficiency bi-directional DC-DC converters. In order to allow for quasi-direct measurement of the lost power, the concept is to operate the converter by input current having constant module, handling alternating energy flow between two large capacitor banks at given input/output DC voltages. Accordingly, the input current reference is a low frequency (65 Hz) rectangular-wave, whose duty-cycle is regulated by suitable voltage loop due to constant module operation. Except for added large capacitor banks' losses and other secondary effects related to 65 Hz operation, the input DC power supply is shown equivalent to conversion losses at given DC working point. The results point-out the high efficiency of the conversion structure well matched with simple analytical models.","PeriodicalId":405648,"journal":{"name":"Proceedings of IEEE International Conference on Industrial Technology 2000 (IEEE Cat. No.00TH8482)","volume":"33 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":"131378192","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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