2009
41
2
2
71
Active Filter Control Method Based on Direct Power Control for Compensating Reactive Powers due to Unbalanced Voltages and Nonlinear Loads
Active Filter Control Method Based on Direct Power Control for Compensating Reactive Powers due to Unbalanced Voltages and Nonlinear Loads
2
2
Active filters have proven to be more effective than passive techniques to improve power quality and to solve harmonic and power factor problems due to nonlinear loads. This paper proposes a control scheme based on the instantaneous active and reactive power. The inverter of this active filter is a threephase, twolevel converter. Space vector technique is used as modulators and pattern generators for the Pulse Width Modulated converter. Virtual Flux and a Phase Locked Loop based on a Double Synchronous Reference Frame cause this control system be resistant to the majority of line voltage disturbances. Good dynamic response, independent control of active and reactive powers and also unity power factor of converter are advantages of the proposed method. The operation of the proposed control strategy is verified in MATLAB simulation environment
1
Active filters have proven to be more effective than passive techniques to improve power quality and to solve harmonic and power factor problems due to nonlinear loads. This paper proposes a control scheme based on the instantaneous active and reactive power. The inverter of this active filter is a threephase, twolevel converter. Space vector technique is used as modulators and pattern generators for the Pulse Width Modulated converter. Virtual Flux and a Phase Locked Loop based on a Double Synchronous Reference Frame cause this control system be resistant to the majority of line voltage disturbances. Good dynamic response, independent control of active and reactive powers and also unity power factor of converter are advantages of the proposed method. The operation of the proposed control strategy is verified in MATLAB simulation environment
1
8


E.
Abirii
Corresponding Author, E. Abiri is with the Department of Electrical Engineering, Shiraz University of Technology (SUTECH), Shiraz, Iran (emil:
abiri@sutech.ac.ir)
Corresponding Author, E. Abiri is with the
Iran


M.R.
Salehiii
M. R. Salehi is with the Department of Electrical Engineering, Shiraz University of Technology (SUTECH), Shiraz, Iran (emil:
salehi@sutech.ac.ir)
M. R. Salehi is with the Department of Electrical
Iran


A.
Abrishamifariii
A. Abrishamifar is with the Department of Electrical Engineering, Iran University of Science and Technology (IUST), Tehran, Iran, (email:
abrishamifar@iust.ac.ir)
A. Abrishamifar is with the Department of
Iran
active filter
DPC
Power Quality
harmonics
[[1] Rahmati A.; Abrishamifar A.; Abiri E.; “Space vector modulation direct power control in an inverter connected to grid and wind turbine”, In Persian, fourteenth electrical conference, Iran, May 2006. ##[2] Malinowski M.; “Sensorless control strategies for threephase PWM rectifiers”, Ph.D. dissertation, Inst. Control Ind. Electron., Warsaw Univ. Technol., Warsaw, Poland, 2001. ##[3] Noguchi T.; Tomiki H.; Kondo S.; TakahashiI.; “Direct power control of PWM converter without powersource voltage sensors”, IEEE Trans. Ind. Applicat., vol.34, pp.473479, May/June 1998. ##[4] Peng F., Z.; Ott G., W.; Adams D., J.; “Harmonic and reactive power compensation based on the generalized instantaneous reactive theory for threephase fourwire systems”, IEEE Trans. Power Elec., vol.13, pp.11741181, Nov.1998. ##[5] Kwon B., H.; Lim J., H.; “A linevoltagesensorless synchronous rectifier”, IEEE Trans. Ind. Applicant, vol.14, pp.966972, sept.1999. ##[6] Chen S.; Joos G.; “Direct power control of active filters for voltage flicker mitigation”, Ind. Appl. Conference, Thirtysixth IAS Annual Meeting, pp.26832690, September/October 2001. ##[7] Cichowias M.; Malinoaski M.; Kazmierkowski M., P.; Sobczuk D., L.; Rodrigues P.; Pou J.; “Active filtering function of threephase PWM Boost rectifier under different line voltage conditions”, IEEE Trans. On Ind. Elec., vol.52, no.2, pp.410419, April 2005. ##[8] Ohnishi T.; “Threephase PWM converter/inverter by means of instantaneous active and reactive power control”, IECON’91, pp.819824, 1991. ##[9] Rodriguez P.; Bergas J.; Pou J.; Candela I.; Burgos R.; Boroyevich D.; “Double synchronous reference frame PLL for power converters control”, IEEE 36th. conf. on power electronic specialists, pp.14151421, 2005. ##]
ISAR Image Improvement Using STFT Kernel Width Optimization Based On Minimum Entropy Criterion
ISAR Image Improvement Using STFT Kernel Width Optimization Based On Minimum Entropy Criterion
2
2
Nowadays, Radar systems have many applications and radar imaging is one of the most important of these applications. Inverse Synthetic Aperture Radar (ISAR) is used to form an image from moving targets. Conventional methods use Fourier transform to retrieve Doppler information. However, because of maneuvering of the target, the Doppler spectrum becomes timevarying and the image is blurred. Joint TimeFrequency Transforms (JTFT) like ShortTime Fourier Transform (STFT) can resolve the Doppler spectrum and reduce the image blurring. These transforms use some kernels for signal spectrum analysis. According to the uncertainty principle, the proper selection of this kernel and its parameters could affect the quality of the image. In this paper, using a conventional kernel for STFT, i.e. Gaussian kernel, we use minimum entropy criterion to optimize the kernel duration. Simulation results show that this optimization can improve the constructed image compared with the Fourier transform method.
1
Nowadays, Radar systems have many applications and radar imaging is one of the most important of these applications. Inverse Synthetic Aperture Radar (ISAR) is used to form an image from moving targets. Conventional methods use Fourier transform to retrieve Doppler information. However, because of maneuvering of the target, the Doppler spectrum becomes timevarying and the image is blurred. Joint TimeFrequency Transforms (JTFT) like ShortTime Fourier Transform (STFT) can resolve the Doppler spectrum and reduce the image blurring. These transforms use some kernels for signal spectrum analysis. According to the uncertainty principle, the proper selection of this kernel and its parameters could affect the quality of the image. In this paper, using a conventional kernel for STFT, i.e. Gaussian kernel, we use minimum entropy criterion to optimize the kernel duration. Simulation results show that this optimization can improve the constructed image compared with the Fourier transform method.
9
16


M.
ModarresHashemi
M. ModarresHashemi is with the ECE Department of Isfahan University of Technology, Isfahan, Iran (email: modarres@cc.iut.ac.ir)
M. ModarresHashemi is with the ECE Department
Iran


M.
Dorostgan
M. Dorostgan is with the ECE Department of Isfahan University of Technology, Isfahan, Iran ( email:mdorostgan@alumni.iut.ac.ir)
M. Dorostgan is with the ECE Department of
Iran


M. M.
Naghshiii *
Corresponding Author, M. M. Naghsh is with the ECE Department of Isfahan University of Technology, Isfahan, Iran
(email: mm_naghsh@ec.iut.ac.ir)
Corresponding Author, M. M. Naghsh is with
Iran
Imaging Radar
ISAR
Joint TimeFrequency Transform
Entropy
Normalized correlation
[[1] Gonzales, R. C.; Woods, R. C.; digital image processing, 2nd Edition, Prentice Hall, 2002. ##[2] Mensa, D. L.; High resolution radar crosssection imaging, 2nd Edition, Artech house, 1991. ##[3] Wehner, D. R.; High resolution radar ,2nd Edition , ##Artech house , 1994. ##[4] Chen, V. ; Ling, H.; TimeFrequency transform for radar imaging and signal analysis, Artech house, 2002. ##[5] Son,S. J.;Thmas, G.;Flore, C. B.;Range Doppler radar imaging and motion compensation, Artech house, 2000. ##[6] Xi, L. ;Guosui, L. ; Ni, J.; “Autufocusing of image based on entropy minimization”, IEEE Transaction on Aerospace and Electronic Systems, Vol. 35,No.4 ,pp. 12401251, 1999. ##[7] Chen, V., Qian, S. ; “Joint timefrequncy transform for radar range dopller imaging” , IEEE Transaction on Aerospace and Electronic Systems, Vol. 34, No. 2,pp. ##[8] Chen, V. ;”Reconstruction of inverse synthetic aperture radar image using adaptive timefrequency wavelet transform”, SPIE Proc. On wavelet Applications, Vol.2494 pp. 373386, 1995. ##[9] Kersten, P.R.; Jansen, R.W.; Luc, K.; Ainsworth, T.L.; “Implementation of the timefrequency distribution series for SAR applications”, Proceedings of IEEE International Conference on Geosciences and Remote Sensing Symposium, pp. 35873590, 2006. ##[10] Zhu, Y.; Wang, H.; Xiao, S.; “Application of Adaptive Kernel TimeFrequency Distribution in ISAR”, 9th International Conference on Signal Processing, 2008. ##[11] Oppenheim, A. V.; Schafer, R. W.; Buck, J. R.; Discrete time signal processing, 2nd Edition, Prentice Hall, 1999. ##[12] M. Dorostgan; Joint timefrequency transfoms for ISAR imaging, M.Sc Thesis (In Persian), ECE Department, Isfahan University of Technology, 2004, (in Persian).. ##[13] Ho, R. J.; Hyo, T. K.; Kyung, T. K.; “Application of Subarray Averaging and Entropy Minimization Algorithm to SteppedFrequency ISAR Autofocus”, IEEE Transaction on antennas and propagation, Vol. 56, No. 4, 2008. ##[14] Zhu, D.; Wang, L.; Yu, Y.; Tao, Q.; Zhu, Z.; “Robust ISAR range alignment via minimizing the entropy of the average range profile”, IEEE Geoscience and remote Sensing letter, vol. 6, no. 2, pp. 204–208, Apr. 2009. ##[15] Cao, P.; Xing, M.; Sun, G.; Li, Y.; Bao, Z.; “Minimum Entropy via Subspace for ISAR Autofocus”, IEEE geoscience and remote sensing letters, Vol. PP, pp. 15, 2009. ##[16] Martorella, M.; Berizzi, F.; Bruscoli, S.; “Use of Genetic Algorithms for Contrast and Entropy Optimization in ISAR Autofocusing”, EURASIP Journal on Applied Signal Processing, 2006.E. H. Miller, "A note on reflector arrays," IEEE Trans. Antennas Propagat., to be published. ##[17] M. Dorostgan, M. ModarresHashemi, S. Sadri; Optimizing STFT based ISAR image formation using entropy and contrast criteria, ICEE, 2005, (in Persian). ##[18] Cover, T. M. ;Thomas, J. A. ; Elements of information theory, John Wiley & sons, 1991. ##[19] Chen, V.;Miceli, W. J. ; “Simulation of Isar imaging of moving targets”, IEE proc.Radar, sonar and navigation, Vol. 148, No.3, pp. 160166, 2001. ##[20] Hua, Y. ; Baqai, E. ; Zhu, Y. ; “Imaging of point scatterers from stepfrequency ISAR data”, IEEE Transaction on Aerospace and Electronic Systems, Vol. 29,No. 1,pp. 195204, 1993. ##[21] Shirman, Y. D. ;Computer simulation of aerial target radar scattering, recognition, detection and tracking, Artech house, 2002. ##[22] Zwieg, G.; “Superresolution Fourier transforms by optimisation, and ISAR imaging”, IEE Proc.Radar ,Sonar and navigation, Vol. 150, No. 4, 2003. ##[23] Popovic, V.; Thayaparan, T.; Stankovic, L.; “Noise analysis of the high resolution methods in ISAR”, Proceedings of the 4th International Symposium on Image and Signal Processing and Analysis, 2005. ##[24] Kovaci, M.; Isar, D.; Isar, A.; “Denoising SAR images”, International Symposium on Signals, Circuits and Systems, 2003. ##[25] Nuthalapati, M. R. ; “High resolution construction of ISAR images”, IEEE transaction on aerospace and electronic, Vol. 28, No. 2, 1992. ##Naghsh, M. M.; ModarresHashemi, M. “ISAR Image Formation Based on Minimum Entropy Criterion and Fractional Fourier Transform”, IEICE transaction on communication, Vol. E92B, No. 8, pp. 27142722, 2009##]
A Solution to View Management to Build a Data Warehouse
A Solution to View Management to Build a Data Warehouse
2
2
Several techniques exist to select and materialize a proper set of data in a suitable structure that manage the queries submitted to the online analytical processing systems. These techniques are called view management techniques, which consist of three research areas: 1) view selection to materialize, 2) query processing and rewriting using the materialized views, and 3) maintaining materialized views. There are several parameters should be considered in order to find the most important algorithm for view management. As various researches have been done to propose view selection algorithms, we should select and modify the most suitable algorithm for view materialization based on the properties of the applications. In this paper, we investigate and find relevant parameters to view selection algorithms and classify them based on these parameters. We also present a system to evaluate algorithms and compare them with respect to the values of the evaluation parameters. Based on the results of these activities, we propose a roadmap that helps us choose the most efficient view selection algorithm concerning application types.
1
Several techniques exist to select and materialize a proper set of data in a suitable structure that manage the queries submitted to the online analytical processing systems. These techniques are called view management techniques, which consist of three research areas: 1) view selection to materialize, 2) query processing and rewriting using the materialized views, and 3) maintaining materialized views. There are several parameters should be considered in order to find the most important algorithm for view management. As various researches have been done to propose view selection algorithms, we should select and modify the most suitable algorithm for view materialization based on the properties of the applications. In this paper, we investigate and find relevant parameters to view selection algorithms and classify them based on these parameters. We also present a system to evaluate algorithms and compare them with respect to the values of the evaluation parameters. Based on the results of these activities, we propose a roadmap that helps us choose the most efficient view selection algorithm concerning application types.
17
27


N.
Daneshpour
Corresponding Author, N. Daneshpour is a PhD candidate of the Department of Computer Engineering & Information Technology, Amirkabir
University of Technology, Tehran, Iran (email: daneshpour@aut.ac.ir).
Corresponding Author, N. Daneshpour is a
Iran


A.
Abdollahzadeh Barfourosh
A. Abdollahzadeh Barfourosh is with the Department of Computer Engineering & Information Technology, Amirkabir University of
Technology, Tehran, Iran (email: ahmad@ce.aut.ac.ir).
A. Abdollahzadeh Barfourosh is with the Department
Iran
Algorithm classification
data warehousing
view management
view materialization
view selection
[[1] Agrawal S., Chaudhuri S., Narasayya V.; “Automated Selection of Materialized Views and Indexes for SQL Databases”, 26th International Conference on Very Large Databases, Cairo, Egypt, pp. 496505, 2000. ##[2] Agrawal S., Chaudhuri S., Kollar L., Marathe A., Narasayya V., Syamala M.; “Database Tuning Advisor for Microsoft SQL Server 2005”, 30th VLDB Conference, Toronto, Canada, pp. 11101121, 2004. ##[3] Agrawal S., Narasayya V., Yang B.; “Integrating Vertical and Horizontal Partitioning into Automated Physical Database Design”, SIGMOD 2004, Paris, France, pp. 359370, 2004. ##[4] Aouiche K., Darmont J.; “Data miningbased materialized view and index selection in data warehouses”, Journal of Intelligent Information System (2009) 33:65–93, 2009. ##[5] Aouiche K., Jouve P. E., Darmont J.; “ClusteringBased Materialized View Selection in Data Warehouses”, 10th EastEuropean Conference on Advances in Databases and Information Systems (ADBIS06), Thessaloniki, Greece, 2006. ##[6] Asgharzadeh Talebi Z., Chirkova R., Fathi Y., Stallmann M.; “Exact and Inexact Methods for Selecting Views and Indexes for OLAP Performance Improvement”, EDBT ’08, March 2530, 2008, Nantes, France, pp. 311322, 2008. ##[7] Bellahsene Z., Marot P.; “Materializing a Set of Views: Dynamic Strategies and Performance Evaluation”, 2000 International Symposium on Database Engineering & Applications, IEEE , pp. 424428, 2000. ##[8] Chan G.K.Y., Li Q., Feng L.; “Design and Selection of Materialized Views in a Data Warehousing Environment: A Case Study”, DOLAP99, Kansas City MO USA, pp. 4247, 1999. ##[9] Chaudhuri S., Narasayya V.; “An Efficient, CostDriven Index Selection Tool for Microsoft SQL Server”, 23rd VLDB Conference Athens, Greece, pp. 146155, 1997. ##[10] Chirkova R., Halevy A.Y., Suciu D.; “A formal perspective on the view selection problem”, The VLDB Journal (2002) 11, pp. 216–237, 2002. ##[11] Chirkova R., Li C.; “Answering queries using materialized views with minimum size”, The VLDB Journal (2006) 15(3) pp. 191–210, 2006. ##[12] Chirkova R., Li C.; “Materializing Views with Minimal Size to Answer Queries”, PODS’03, San Diego, CA, pp. 3848, 2003. ##[13] Choi C. H., Yu J. X., Lu H.; “Dynamic Materialized View Management Based on Predicates”, Springer, APWeb 2003, LNCS, pp. 583594, 2003. ##[14] Daneshpour N., Abdollahzadeh Barfourosh A.; “AUTQPM: The New Framework to Query Evaluation for Data Warehouse Creation”, Iranian Journal of Electrical and Computer Engineering Vol. 6, N. 1, pp. 3545, 2008. ##[15] Daneshpour N., Abdollahzadeh Barfourosh A.; “View Selection Algorithms to Build Data Warehouse”, Technical Report: AIS Lab, IT & Computer Engineering Department, Amirkabir University of Technology, CE/ TR.DS/ 86/ 01, http://ceit.aut.ac.ir/~daneshpour/Publications.htm, 2008. ##[16] Ezeife C.I.; “Selecting and materializing horizontally partitioned warehouse Views”, Data & Knowledge Engineering 36, pp. 185210, 2001. ##[17] Gong A., Zhao W.; “Clusteringbased Dynamic Materialized View Selection Algorithm”, Fifth International Conference on Fuzzy Systems and Knowledge Discovery, IEEE, pp. 391395, 2008. ##[18] Gupta H.; “Selection of Views to Materialize in a Data Warehouse”, In Intl. Conf. On Database Theory, Delphi, Greece, pp. 98112, 1997. ##[19] Gupta H., Mumick I.S.; “Selection of Views to Materialize in a Data Warehouse”. IEEE Trans. Knowledge and Data Engineering, Volume 17, Issue 1, pp. 24 – 43, 2005. ##[20] Han J., Kamber M.; Data Mining: Concepts and Techniques, Second Edition, Morgan Kaufmann Publishers, 2006. ##[21] Hanusse N., Maabout S., Tofan R.; “A view selection algorithm with performance guarantee”, EDBT 2009, March 24–26, 2009, Saint Petersburg, Russia. pp. 946957, 2009. ##[22] Harinarayan V., Rajaraman A., Ullman J.D.; “Implementing Data Cubes Efficiently”, SIGMOD'96 6/96 Montreal, Canada, pp. 205216, 1996. ##[23] Hung M.C., Huang M.L., Yang D.L., Hsueh N.L.; “Efficient approaches for materialized views selection in a data warehouse”, ELSEVIER Trans. Information Sciences 177, pp. 1333–1348, 2007. ##[24] Kalnis P., Mamoulis N., Papadias D.; “View Selection Using Randomized Search”, ELSEVIER Trans. Data & Knowledge Engineering, vol. 42, pp. 89–111, 2002. ##[25] Kotidis Y., Roussopoulos N.; “A Case for Dynamic View Management”, ACM Transactions on Database Systems, Vol. 26, No. 4, pp. 388–423, 2001. ##[26] Kotidis Y., Roussopoulos N.; “DynaMat: A Dynamic View Management System for Data Warehouses”, SIGMOD’99 Philadelphia PA, pp. 371382, 1999. ##[27] Lawrence M.; “Multiobjective Genetic Algorithms for Materialized View Selection in OLAP Data Warehouses”, GECCO’06, Seattle, Washington, USA, pp. 699706, 2006. ##[28] Lawrence M., RauChaplin A.; “Dynamic View Selection for OLAP”, DaWak 2006, LNCS 4081, Springer, pp. 3444, 2006. ##[29] Liang W., Wang H., Orlowska M.E.; “Materialized view selection under the maintenance time constraint”, Data & Knowledge Engineering 37, pp. 203216, 2001. ##[30] Liu Y. C., Hsu P. Y., Sheen G. J., Ku S., Chang K. W.; “Simultaneous determination of view selection and update policy with stochastic query and response time constraints”, Information Sciences 178 (2008) 3491–3509, 2008. ##[31] Mahboudi H., Aouiche K., Darmon J.; “Materialized View Selection by Query Clustering in XML Data Warehouses”, 4th International Multiconference on Computer Science and Information Technology (STIC 06), Amman, Jordan, 2006. ##[32] Nadeau T.P., Teorey T.J.; “Achieving Scalability in OLAP Materialized View Selection”, DOLAP ’02, McLean, Virginia, USA, pp. 2834, 2002. ##[33] Neapolitan R. “Fundamentals of Algorithms Using C++ Pseudocode”, Jones and Bartlett Publishers, Inc.; 3rd edition, 2003. ##[34] Phan T., Li W. S.; “Dynamic Materialization of Query Views for Data Warehouse Workloads”, ICDE 2008, IEEE, pp. 436445, 2008. ##[35] Ramachandran K., Shah B., Raghavan V.; “Access PatternBased Dynamin Prefetching of Views in an OLAP System”, International Conference on Enterprise Information Systems, 2005. ##[36] Shah B., Ramachandran K., Raghavan V.; “A Hybrid Approach for Data Warehouse View Selection”, International Journal of Data Warehousing and Mining, Vol. 2, Issue 2, 2006. ##[37] Shukla A., Deshpande P.M., Naughton J.F.; “Materialized View Selection for Multidimensional Datasets”, VLDB, Morgan Kaufmann, pp. 488499, 1998. ##[38] Souza M.F.D., Sampaio M.C.; “Efficient Materialization and Use of Views in Data Warehouses”, SIGMOD Record, Vol. 28, No. 1, pp. 7883, 1999. ##[39] Theodoratos D., Sellis T.; “Designing Data Warehouses”, Data & Knowledge Engineering 31, pp. 279301, 1999. ##[40] Theodoratos D., Bouzeghoub M.; “A General Framework for the View Selection Problem for Data Warehouse Design and Evolution”, DOLAP '00 11/00 McLean, VA, USA, pp. 18, 2000. ##[41] Theodoratos D., Ligoudistianos S., Sellis T.; “View Selection for Designing the Global Data Warehouse”, Data & Knowledge Engineering 39, pp. 219240, 2001. ##[42] Theodoratos D., Xu W.; “Constructing Search Spaces for Materialized View Selection”, DOLAP’04, Washington, DC, USA, pp. 112121, 2004. ##[43] Turban E., Aronson J.E., Liang T.P., Sharda R.; Decision Support and Business Intelligence Systems, 8nd Edition, Prentice Hall, 2006. ##[44] Uchiyama H., Runapongsa K., Teorey T.J.; “A Progressive View Materialization Algorithm”, DOLAP99, Kansas City MO USA, pp. 3641, 1999. ##[1] Valluri S.R., Vadapalli S., Karlapalem K.; “View Relevance Driven Materialized View Selection in Data Warehousing Environment”, ADC2002, vol. 5, pp. 187196, 2002. ##[2] Xu W., Theodoratos D., Zuzarte C.; “Computing Closest Common Subexpressions for View Selection Problems”, DOLAP’06, Arlington, Virginia, USA, pp. 7582, 2006. ##[3] Xu W., Theodoratos D., Zuzarte C.; “A Dynamic View Materialization Scheme for Sequences of Query and Update Statements”, DaWaK 2007, LNCS 4654, pp. 5565, 2007. ##[4] Yu J.X., Yao X., Choi C.H., Goa G.; “Materialized View Selection as Constrained Evolutionary Optimization”, IEEE Transactions on Systems, Man and CyberneticsPart C: Applications and Reviews, vol. 33, no. 4, pp. 458467, 2003. ##[5] Zhang C., Yang J., Kalapalem K.; “Dynamic Materialized View Selection in Data Warehouse Environment”, Informatica (Slovenia), volume 27, number 1, pp. 451460, 2003. ##]
A Quantitative Evaluation of Maintainability of Software Architecture Styles
A Quantitative Evaluation of Maintainability of Software Architecture Styles
2
2
Proper decisions play a crucial role in any software architecture design process. An important decision of design stage is the selection of a suitable software architecture style. Lack of investigation on the quantitative impact of architecture styles on software quality attributes is the main problem in using such styles. Consequently, the use of architecture styles in designing is based on the intuition of software developers. The aim of this research is to quantify the impacts of architecture styles on software maintainability that is an expected quality of each software. In this study, architecture styles are quantified based on coupling, complexity and cohesion metrics and ranked by analytic hierarchy process from a maintainability viewpoint. Metrics validation confirms fitness of the metrics. Regarding the great impact of this decision on maintainability of software product, the presented parametric model provides a basis for sensible selection of architecture style.
1
Proper decisions play a crucial role in any software architecture design process. An important decision of design stage is the selection of a suitable software architecture style. Lack of investigation on the quantitative impact of architecture styles on software quality attributes is the main problem in using such styles. Consequently, the use of architecture styles in designing is based on the intuition of software developers. The aim of this research is to quantify the impacts of architecture styles on software maintainability that is an expected quality of each software. In this study, architecture styles are quantified based on coupling, complexity and cohesion metrics and ranked by analytic hierarchy process from a maintainability viewpoint. Metrics validation confirms fitness of the metrics. Regarding the great impact of this decision on maintainability of software product, the presented parametric model provides a basis for sensible selection of architecture style.
29
38


G.R.
Shahmohammadii
G.R. Shahmohammadi is Ph.D. of Computer Engineering, Tarbiat Modares University, Tehran, Iran (email: Shahmohamadi@modares.ac.ir)
G.R. Shahmohammadi is Ph.D. of Computer Engineerin
Iran


S.
Jalili
Corresponding Author, S. Jalili is with the Department of Computer Engineering, Tarbiat Modares University, Tehran, Iran (email:
Sjalili@modares.ac.ir)
Corresponding Author, S. Jalili is with the
Iran
Software Architecture
Architectural Style
Coupling
Complexity
Cohesion
Maintainability Evaluation
[[1] L. Bass, P. Clements, and R. Kazman,"Software Architecture in Practice" (2nd Edition), AddisonWesley, 2003, p. 89. ##[2] F. Buschmann, R. Meunier, H. Rohnert, P. Sornmerlad, and M. Stal, "PatternOriented Software Architecture A system of Patterns", John Wiley & Sons, 1996, p. 394. ##[3] C. Seo, G. Edwards, S. Malek, and N. Medvidovic," A Framework for Estimating the Impact of a Distributed Software System’s Architectural Style on Its Energy Consumption", 7th Working IEEE/IFIP Conf. on Software Architecture, 2009, pp. 277280. ##[4] B. Harrison, and P. Avgeriou, "Leveraging Architecture Patterns to Satisfy Quality Attributes", 1st European Conf. on Software Architecture, Springer, pp. 263270, 2007. ##[5] P. Avgeriou P, and U. Zdun, "Architectural Patterns Revisited: A Pattern Language", Proc. of 10th European Conf. on Pattern Languages of Programs، 2005, pp.139. ##[6] J.S Kim, and D. Garlan, "Analyzing Architectural Styles with alloy", Proc. of the ISSTA 2006 workshop on Role of Software Architecture for Testing and Analysis, 2006, pp. 7080. ##[7] R. Bruni, A. Bucchiarone, A. Gnesi, D. Hirsch, and A.L. Lafuente,"Graphbased Design and Analysis of Dynamic Software Architectures", LNCS 5065, pp. 37–56, 2008. ##[8] H. Reza, and E. Grant, "QualityOriented Software Architecture", The IEEE Int. Conf on Information Technology, 2005, pp. 140 – 145. ##[9] G.R. Shahmohammadi, and S. Jalili,"ScenarioBased Quantitative Evaluation of Software Architecture Style from Maintainability Viewpoint", 14 th Annual of CSI Computer Conference (CSICC 2009), Iran, Amirkabir University, 2009. ##[10] H. Grahn, and J. Bosch,"Some Initial Performance Characteristics of Three Architectural Styles", Proc. of Int. Workshop on Software and Performance, 1998. ##[11] D. Garlan, and S. Khersonsky, "Model Checking Implicit Invocation Systems", 10th Int. Workshop On Software Specification and Design, 2000. ##[12] M. Shaw, D. Garlan, "Software Architecture: PerspectivesDiscipline on an ٍEmerging Discipline”, Prentice Hall, 1996. ##[13] L. Briand, S. Morasca, and V. Basili, "Property Based Software Engineering Measurement", IEEE Trans on Software Eng., Vol. 22, No. 1, pp. 6886, 1996. ##[14] L. Briand, J. Wust, and H. Lounis, "Using Coupling Measurement for Impact Analysis in ObjectOriented Systems", IEEE Int. Conf. on Software Maintenance, 1999. ##[15] S.L. Pfleeger, and J.M. Atlee,”Software Engineering, Theory and Practice”, 3rd Edition, Prentice Hall, 2006. ##[16] P. Yu, T. Systa, and H. Muller, "Predicting FaultProneness using OO Metrics. An Industrial Case Study," 6th European Conf. on Software Maintenance and Reengineering, 2002, pp.99 – 107. ##[17] M. Alshayeb, and L. Wei, "An Empirical Validation of ObjectOriented Metrics in Two Different Iterative Software Processes," IEEE Trans on Software Engineering, Vol. 29 (11), pp. 1043 – 1049, 2003. ##[18] F. Bachmann, L. Bass, M. Klein, M. and C. Shelton, “Designing Software Architectures to Achieve Quality Attribute Requirements”, IEE Proc. of Software, Vol. 152, No 4,pp. 153 165, 2005. ##[19] E. Weyuker, "The Evaluation of Software Complexity Measures", IEEE Trans on Soft. Eng, 14, pp. 13571365, 1988. ##[20] C.L. Hwang, K. Yoon, "Multiple AttributeDecision Making", SpringerVerlag, 1981. ##[21] T. L. Saaty, and L. G. Vargas, “Models, Methods, Concepts & Applications of the Analytic Hierarchy Process”, Kluwer Academic Publisher, 2001. ##[22] L. Bass, P. Clements, and R. Kazman," Software Architecture in Practice", AddisonWesley, 1998, p. 17. ##[23] ISO, International Organization for Standardization, “ISO91261:2001, Software Engineering – Product quality, Part 1: Quality model”, 2001. ##[24] E. Yourdon, and L. Constantine, "Structured Design", Englewood Cliff, NJ, prentice Hall,1978. ##[25] N. Fenton, and A. Melton, "Deriving Structurally Based Software Measures", Journal of Systems and Software 12(3), pp. 177187, 1990. ##[26] M. J. Shepperd, and D.C. Ince, "The use of metrics in the early detection of design errors", Proc.of the European Software Engineering Conf, 1990, pp.6785. ##[27] NE. Fenton, and SL. Pfleeger,"Software Metrics: A Rigorous and Practical Approach", (2nd Edition), International Thomson Computer PRESS, 1997. ##[28] S. Chidamber, and C. Kemerer,"A Metrics Suite for Object Oriented Design", IEEE Trans on Software Engineering, Vol. 20, pp. 476493, 1994. ##[29] L. Yu, and S. Ramaswamy, "Component Dependency in ObjectOriented Software", Journal of Computer Science and Technology, 22(3), pp. 379386, 2007.##]
Voltage Coordination of FACTS Devices in Power Systems Using RLBased MultiAgent Systems
Voltage Coordination of FACTS Devices in Power Systems Using RLBased MultiAgent Systems
2
2
This paper describes how multiagent system technology can be used as the underpinning platform for voltage control in power systems. In this study, some FACTS (flexible AC transmission systems) devices are properly designed to coordinate their decisions and actions in order to provide a coordinated secondary voltage control mechanism based on multiagent theory. Each device here is modeled as an agent being able to cooperate and communicate with other devices. In this system, individual autonomous agents and intelligent decision makers learn to perform optimal actions through proper interactions with their environments. The SARSA Qlearning, which is an onpolicy algorithm in reinforcement learning (RL) is then used and tested successfully in voltage control problem. In this research, the Java Agent DEvelopment (JADE) platform is used to implement the agents and to simulate their communications. The power system is also fully implemented in Java. The proposed intelligent MA based method is finally applied to IEEE 39buses New England power system. The results of simulation better highlight the merit of the method and its ability in coordinating FACTS devices for removing voltage disturbances.
1
This paper describes how multiagent system technology can be used as the underpinning platform for voltage control in power systems. In this study, some FACTS (flexible AC transmission systems) devices are properly designed to coordinate their decisions and actions in order to provide a coordinated secondary voltage control mechanism based on multiagent theory. Each device here is modeled as an agent being able to cooperate and communicate with other devices. In this system, individual autonomous agents and intelligent decision makers learn to perform optimal actions through proper interactions with their environments. The SARSA Qlearning, which is an onpolicy algorithm in reinforcement learning (RL) is then used and tested successfully in voltage control problem. In this research, the Java Agent DEvelopment (JADE) platform is used to implement the agents and to simulate their communications. The power system is also fully implemented in Java. The proposed intelligent MA based method is finally applied to IEEE 39buses New England power system. The results of simulation better highlight the merit of the method and its ability in coordinating FACTS devices for removing voltage disturbances.
39
49


M. R.
Tousii
Corresponding Author, M. R. Tousi is PhD student in Department of Electrical Engineering, Amirkabir University of Technology, Tehran, Iran
(email: smr_tousi@yahoo.com).
Corresponding Author, M. R. Tousi is PhD
Iran


S. H.
Hosseinianii
S. H. Hosseininan is with the Department of Electrical Engineering, Amirkabir University of Technology, Tehran, Iran (email:
Hosseininan@aut.ac.ir).
S. H. Hosseininan is with the Department
Iran


Mohammad B
Menhaji
M. B. Menhaj is with the Department of Electrical Engineering, Amirkabir University of Technology, Tehran, Iran (email: tmenhaj@ieee.org).
M. B. Menhaj is with the Department of Electrical
Iran
MultiAgent Systems (MAS)
Secondary Voltage Control
Voltage Coordination
Reinforcement Learning
Java Agent Development (JADE) Framework
[[1] H. Lefebvre, D. Fragnier, and J. Y. Boussion, “Secondary coordinated voltage control system: Feedback of EDF”, in Proc. IEEE/PES Summer Meeting, Seattle, USA, July, 2000, pp. 291295. ##[2] H. F. Wang, “Multiagent coordination for the secondary voltage control in power system contingencies,” in Proc. Inst. Elect. Eng. C, 2001, pp. 61–66. ##[3] Hai Feng Wang,, H. Li, and H. Chen “Coordinated Secondary Voltage Control to Eliminate Voltage Violations in Power System Contingencies,” IEEE Trans. on Power Systems, Vol. 18, No. 2, May 2003. ##[4] J. P. Paul, J. Y. Leost, and J. M. Tesseron, “Survey of the secondary voltage control in France: present realization and investigation”, IEEE Trans. on Power System, 2 (2), 1987, pp. 505511. ##[5] J. P. Paul and J. Y. Leost, “Improvements of the secondary voltage control in France,” in IFAC Symp. on Power Syst. Power Plants Control, Beijing, China, 1986. ##[6] Mats Larsson, “Coordinated Voltage Control in Electric Power Systems,” Doctoral Dissertation, Lund University, Sweden, 2000, pp5560. ##[7] Sheng Gehao, Jiang Xiuceng, and Zeng Yi , “Optimal Coordination For MultiAgent Based Secondary Voltage Control in Power System,” IEEE/PES Transmission and Distribution Conference & Exhibition: Asia and Pacific, Dalian, China, 2005. ##[8] JADE – Java Agent DEvelopment Framework, see: http://jade.tilab.com/ ##[9] Foundation for Intelligent Physical Agents (FIPA), see: http://www.fipa.org/. ##[10] D. P. Bertsekas and J. N. Tsitsiklis, NeuroDynamic Programming. Belmont, MA: Athena Scientific, 1996. ##[11] L. P. Kaelbling, M. L. Littman, and A. W. Moore, “Reinforcement learning: A survey,” J. Artif. Intell. Res., vol. 4, pp. 237–285, Jan.–June 1996. ##[12] R. S. Sutton and A. G. Barto, “Reinforcement learning: An introduction,” Adaptive Computations and Machine Learning, 1998. ##[13] J. G. Vlachogiannis and N. D. Hatziargyriou, “Reinforcement Learning for Reactive Power Control,” IEEE Trans on Power System, Vol. 19, No. 3, August 2004. ##[14] C.Rehtanz, “Autonomous Systems and Intelligent Agents in Power System Control and Operation” , Springer , ISBN 3540402020. ##[15] Russell, S. J. and Norvig, “Artificial Intelligence: a Modern Approach”, Prentice Hall, 2nd edition, 2003. ##[16] M.Wooldridge, “An Introduction to Multiagent Systems”, Wiley Press, May 2002 ##[17] KAI HUANG, “Shipboard Power System Reconfiguration Using MultiAgent System”, Ph.D. dissertation, Dept. Elec. Eng., The Florida State University, summer 2007. ##[18] J. M. Solanki,N. N. Schulz, “Using Intelligent Multiagent System for Shipboard Power Systems Reconfiguration”, Proceedings of the 13th International Intelligent Systems Application to Power Systems, Nov. 2005. ##[19] D.P. Buse , Q.H.Wu, “ " IP networkbased multiagent systems for industrial automation : information management, condition monitoring and control of power systems”, SPRINGER, 2007, ISBN 9781846286469. ##[20] InterPSS Power System Simulation Project, see: http://www.interpss.org ##[21] Marek Zima, Damien Ernst, “On multiarea control in electric power systems”, Proc. 15th Power System Computation Conference, Liege (Belgium), 2005. ##]
A Modified Hybrid MoMModal Method for Shielding Effectiveness Evaluation of Rectangular Enclosures with Multiple Apertures
A Modified Hybrid MoMModal Method for Shielding Effectiveness Evaluation of Rectangular Enclosures with Multiple Apertures
2
2
A new hybrid modalmoment method is proposed to calculate fields penetrated through small apertures on rectangular metallic enclosures. First, the method of moments is used to numerically solve the governing electric field integral equation for the equivalent twodimensional surfacecurrent distributions on the surface of metallic enclosure including any number of rectangular apertures of arbitrary layout. The resultant exterior scattered fields are then used as the input to a testing procedure to obtain aperture field distributions in the modal expansion technique. These fields can be directly transferred to interior penetrated fields, using appropriate Green’s function of the cavity inside region. To validate the method proposed in this paper, the results of the proposed method are compared with the measurement results available in the literature and those obtained using the conventional modalmoment method for both single and double aperture enclosures. It is shown that the proposed method offers a remarkable improvement in computation burden over the conventional method, especially for calculation of field penetration through much number of apertures typical to realistic measures in the discipline of electromagnetic compatibility.
1
A new hybrid modalmoment method is proposed to calculate fields penetrated through small apertures on rectangular metallic enclosures. First, the method of moments is used to numerically solve the governing electric field integral equation for the equivalent twodimensional surfacecurrent distributions on the surface of metallic enclosure including any number of rectangular apertures of arbitrary layout. The resultant exterior scattered fields are then used as the input to a testing procedure to obtain aperture field distributions in the modal expansion technique. These fields can be directly transferred to interior penetrated fields, using appropriate Green’s function of the cavity inside region. To validate the method proposed in this paper, the results of the proposed method are compared with the measurement results available in the literature and those obtained using the conventional modalmoment method for both single and double aperture enclosures. It is shown that the proposed method offers a remarkable improvement in computation burden over the conventional method, especially for calculation of field penetration through much number of apertures typical to realistic measures in the discipline of electromagnetic compatibility.
51
58


V.
Rezaeii
V. Rezaei (email: vrezaei@hotmail.com),*
V. Rezaei (email: vrezaei@hotmail.com),*
Iran


R.
Moinii
Corresponding Author, R Moini (corresponding author to provide phone: +982166466009, fax:
+982166406469, email: moini@aut.ac.ir)
Corresponding Author, R Moini (corresponding
Iran


S. H. H.
Sadeghii
S. H. H. Sadeghi (email: sadeghi@aut.ac.ir) are with the Electromagnetics Research Laboratory of
Amirkabir University of Technology, 424 Hafez Ave., Tehran 15914, Iran.
S. H. H. Sadeghi (email: sadeghi@aut.ac.ir)
Iran


F
.Rachdiii
F.Rachdi Electromagnetic Compatibility Laboratory, Swiss Federal Institute of Technology (EPFL), Lausanne, Switzerland
F.Rachdi Electromagnetic Compatibility Laboratory,
Iran
Shielding Effectiveness
Hybrid methods
Electric field integral equation
Rectangular enclosures
Rectangular apertures
[[1] C. R. Paul, Introduction to Electromagnetic Compatibility, New Jersey: Wiley, 2006. ##[2] H. A. Mendez, “Shielding theory of enclosures with apertures,” IEEE Trans. Electromagn. Compat., vol. 20, no. 2, pp. 296305, May 1978. ##[3] G. Cerri, R. D. Leo, and V. M. Primiani, “Theoretical and experimental evaluation of the electromagnetic radiation from apertures in shielded enclosures,” IEEE Trans. Electromagn. Compat., vol. 34, no. 4, pp. 423432, Nov. 1992. ##[4] M. P. Robinson, T. M. Benson, C. Christopoulos, J. F. Dawson, M. D. Ganley, A. C. Marvin, S. J. Porter, and D. W. P. Thomas, “Analytical formulation for the shielding effectiveness of enclosures with apertures,” IEEE Trans. Electromagn. Compat., vol. 40, no. 3, pp. 240248, Aug. 1998. ##[5] W. Wallyn, D. D. Zutter, and E. Laermans, “Fast shielding effectiveness prediction for realistic rectangular enclosures,” IEEE Trans. Electromagn. Compat., vol. 45, no. 4, pp. 639643, Nov. 2003. ##[6] C. F. Bunting, “Shielding effectiveness in a twodimensional reverberation chamber using finiteelement techniques,” IEEE Trans. Electromagn. Compat., vol. 45, no. 3, pp. 548552, Aug. 2003. ##[7] D. M. Hockanson, J. L. Drewniak, T. H. Hubing, and T. P. VanDoren, “Application of finitedifference timedomain method to radiation from shielded enclosures,” in Proc. IEEE Int. Symp. on Electromagn. Compat., 2226 Aug., 1994, pp. 8388. ##[8] M. Li, J. Nuebel, J. L. Drewniak, R. E. DuBroff, T. H. Hubing, and T. Van Doren, “EMI from cavity modes of shielding enclosures FDTD modeling and measurement,” IEEE Trans. Electromagn. Compat., vol. 42, no. 1, pp. 2938, Feb. 2000. ##[9] M. D. Deshpande, “Electromagnetic field penetration studies,” NASA/CR2000210297, Jun. 2000. ##[10] Z. A. Khan, C. F. Bunting, and M. D. Deshpande, “Shielding effectiveness of metallic enclosures at oblique and arbitrary polarizations,” IEEE Trans. Electromagn. Compat., vol. 47, no. 1, pp. 112122, Feb. 2005. ##[11] V. Rajamani, C. F. Bunting, M. D. Deshpande, and Z. A. Khan, “Validation of modal/MoM in shielding effectiveness studies of rectangular enclosures with apertures,” IEEE Trans. Electromagn. Compat., vol 48, no. 2, pp. 348353, May 2006. ##[12] W. Wallyn, D. D. Zutter, and H. Rogier, “Prediction of the shielding and resonant behavior of multisection enclosures based on magnetic current modeling,” IEEE Trans. Electromagn. Compat., vol. 44, no. 1, pp. 130138, Feb. 2002. ##[13] Z. B. Zhao, X. Cui, L. Li, and B. Zhang, “Analysis of the shielding effectiveness of rectangular enclosure of metal structures with apertures above ground plane,”, IEEE Trans. Magnetics, vol. 41, no. 5, pp. 18921895, May 2005. ##[14] I. Belokour and J. LoVetri, “A 2D transmission line model for the EM field estimation inside enclosures with apertures,” IEEE Int. Symp. on Electromagn. Compat., vol. 1, 1923 Aug. 2002, pp. 424429. ##[15] J. Paul, V. Podlozny, and C. Christopoulos, “The use of digital filtering techniques for the simulation of fine features in EMC problems solved in the time domain,” IEEE Trans. Electromagn. Compat., vol. 45, no. 2, pp. 238244, May 2003. ##[16] T. Konefal, J. F. Dawson, A. C. Marvin, M. P. Robinson, and S. J. Porter, “A fast circuit model description of the shielding effectiveness of a box with imperfect gaskets or apertures covered by thin resistive sheet coatings,” IEEE Trans. Electromagn. Compat., vol. 48, no. 1, pp. 134144, Feb. 2006. ##[17] P. Sewell, J. D. Turner, M. P. Robinson, D. W. P. Thomas, T. M. Benson, C. Christopoulos, J. F. Dawson, M. D. Ganley, A. C. Marvin, and S. J. Porter, “Comparison of analytic, numerical and approximate models for shielding effectiveness with measurement,” IEE Proc. Sci. Meas. Tech., vol. 145, no. 2, pp. 6166, Mar. 1998. ##[18] J. M. Jin and J. L. Volakis, “A finiteelementboundary integral formulation for scattering by threedimensional cavitybacked apertures,” IEEE Trans. Antennas Propagat., vol. 39, no. 1, pp. 97104, Jan. 1991. ##[19] M. S. Sarto, “Hybrid MFIE/FDTD analysis of the shielding effectiveness of a composite enclosure excited by a transient plane wave,” IEEE Trans. Magnetics, vol. 36, no. 4, pp. 946950, Jul. 2004. ##[20] C. Feng and Z. Shen, “A hybrid FDMoM technique for predicting shielding effectiveness of metallic enclosures with apertures,” IEEE Trans. Electromagn. Compat., vol. 47, no. 3, pp. 456462, August 2005. ##[21] S. M. Rao, D. R. Wilton, and A. W. Glisson, “Electromagnetic scattering by surfaces of arbitrary shape,” IEEE Trans. Antennas Propagat., vol. 30, no. 3, pp. 409418, May 1982. ##[22] C. J. Leat, N. V. Shuley, and G. F. Stickley, “Trianglepath model of bowtie antennas: validation against Brown and Woodward,” IEE Proc. Microwave Antennas Propagat., vol. 145, no. 6, pp. 465470, Dec. 1998.##]
Modeling of Tactile Detection of an Artery in a Soft Tissue by Finite Element Analysis
Modeling of Tactile Detection of an Artery in a Soft Tissue by Finite Element Analysis
2
2
Nowadays, one of the main problems encountered in minimally invasive surgery and telesurgery is the detection of arteries in tissue. In this study, for the first time, tactile detection of an artery in tissue and distinguishing it from the tumor has been modeled by finite element method. In this modeling, three 2D models of tissue have been created: tissue, tissue including a tumor, and tissue including an artery. After solving three models with similar boundary conditions and loadings, first, the 2D tactile mappings and stress graphs for upper nodes of models, which have the role of transferring tactile data, have been explored. Comparing these results, if stress values of nodes are equal and constant, tissue is without tumor or artery. In addition, it was concluded that if stress graph includes a peak, the tissue has a tumor or an artery and that the stress graph of tissue including artery is timedependent in comparison with the tissue including the tumor.
1
Nowadays, one of the main problems encountered in minimally invasive surgery and telesurgery is the detection of arteries in tissue. In this study, for the first time, tactile detection of an artery in tissue and distinguishing it from the tumor has been modeled by finite element method. In this modeling, three 2D models of tissue have been created: tissue, tissue including a tumor, and tissue including an artery. After solving three models with similar boundary conditions and loadings, first, the 2D tactile mappings and stress graphs for upper nodes of models, which have the role of transferring tactile data, have been explored. Comparing these results, if stress values of nodes are equal and constant, tissue is without tumor or artery. In addition, it was concluded that if stress graph includes a peak, the tissue has a tumor or an artery and that the stress graph of tissue including artery is timedependent in comparison with the tissue including the tumor.
59
63


Ali
Abouei Mehrizi
A. Abouei Mehrizi is with the Faculty of Biomedical Engineering, Amirkabir University of Technology, Tehran, Iran
(email: abouei.ali@gmail.com).
A. Abouei Mehrizi is with the Faculty of
Iran


Siamak
Najarian
Corresponding Author, S. Najarian is with the Faculty of Biomedical Engineering, Amirkabir University of Technology, Tehran, Iran
(email: najarian@aut.ac.ir).
Corresponding Author, S. Najarian is with
Iran


Majid
Moiniiii
M. Moini is with Sina Trauma and Surgery Research Center, Tehran University of Medical Sciences, Tehran, Iran
(email: moinim@hotmail.com)
M. Moini is with Sina Trauma and Surgery
Iran
Soft tissue
tumor
artery
tactile detection
Finite Element Method (FEM)
[[1] M. E. H. Eltaib and J. R. Hewit, "Tactile sensing technology for minimal access surgerya review", Mechatronics, vol. 13, p.p. 11631177, 2003. ##[2] W. J. Peine, "Remote palpation instruments for minimally invasive surgery," Ph.D. dissertation, Div. of Eng. and Appl. Sci., HarvardUniversity, 1998. ##[3] J. Dargahi and S. Najarian, "Human tactile perception as a standard for artificial tactile sensing a review”, Inter. J. of Med. Rob. Comp. Ass. Surg., vol. 1, pp. 2335, 2004. ##[4] J. Dargahi and S. Najarian, "Advances in tactile sensors design, manufacturing, and its impact on robotics application  review", Indus. Rob.: An Inter. J., vol. 32/3, pp. 268281, 2005. ##[5] J. Dargahi and S. Najarian, "Human tactile perception as a standard for artificial tactile sensing a review", Inter. J. of Med. Rob. Comp. Ass. Surg., vol. 1, pp. 2335, 2004. ##[6] J. Dargahi and S. Najarian, "A Supported membrane type sensor for medical tactile mapping", Sensor Review, vol. 24, pp. 284297, 2004. ##[7] S. M. Hosseini, S. Najarian, S. Motaghinasab, and J. Dargahi, "Detection of tumors using computational tactile sensing approach", Inter. J. of Med. Rob. Comp. Ass. Surg., vol. 2, no. 4, p.p. 333340, 2006. ##[8] S. M. Hosseini, S. Najarian, S. Motaghinasab, "Analysis of effects of tumors in tissue using of artificial tactile modeling", Amirkabir Journal, to be published. ##S. M. Hosseini, S. Najarian, S. Motaghinasab, and S. Torabi, "Experimental and numerical verification of artificial tactile sensing approach for predicting tumor existence in virtual soft ##]
Design of a Fuzzy Controller Chip with New Structure, Supporting RationalPowered Membership Functions
Design of a Fuzzy Controller Chip with New Structure, Supporting RationalPowered Membership Functions
2
2
In this paper, a new structure possessing the advantages of lowpower consumption, less hardware and highspeed is proposed for fuzzy controller. The maximum output delay for general fuzzy logic controllers (FLC) is about 86 ns corresponding to 11.63 MFLIPS (fuzzy logic inference per second) while this amount of the delay in the designed fuzzy controller becomes 52ns that corresponds to 19.23 MFLIPS. This mixed analog/digital realization of the circuit makes the design programmable and extendable. The proposed controller supports RationalPower Membership Functions with a resolution of 0.03125. Simulation results of the controller using HSPICE simulator level 49 in 0.35um in CMOS process technology (BSIM3v3) show an average power consumption of 4.38mW, and an RMS error of 1.26%. This controller can be used in many applications in which there is a need for a controller chip by correct programming with system experts. Meanwhile the whole area of the chip is 0.0775mm2.
1
In this paper, a new structure possessing the advantages of lowpower consumption, less hardware and highspeed is proposed for fuzzy controller. The maximum output delay for general fuzzy logic controllers (FLC) is about 86 ns corresponding to 11.63 MFLIPS (fuzzy logic inference per second) while this amount of the delay in the designed fuzzy controller becomes 52ns that corresponds to 19.23 MFLIPS. This mixed analog/digital realization of the circuit makes the design programmable and extendable. The proposed controller supports RationalPower Membership Functions with a resolution of 0.03125. Simulation results of the controller using HSPICE simulator level 49 in 0.35um in CMOS process technology (BSIM3v3) show an average power consumption of 4.38mW, and an RMS error of 1.26%. This controller can be used in many applications in which there is a need for a controller chip by correct programming with system experts. Meanwhile the whole area of the chip is 0.0775mm2.
65
71


A.
Naderii
Corresponding Author, A. Naderi is with the Department of Electronic Engineering, urmia University, Urmia, Iran (email:
ali.n.1384@gmail.com).
Corresponding Author, A. Naderi is with the
Iran


H.
Ghasemzadehii
H. Ghasemzadeh, A. Pourazar and M. Aliasghary are with the Department of Electronic Engineering, urmia University, Urmia, Iran (email:
hadi.g.1384@gamil.com, pourazar.alireza@gmail.com, m.aliasghari@gmail.com ).
H. Ghasemzadeh, A. Pourazar and M. Aliasghary
Iran


A.
Pourazar
H. Ghasemzadeh, A. Pourazar and M. Aliasghary are with the Department of Electronic Engineering, urmia University, Urmia, Iran (email:
hadi.g.1384@gamil.com, pourazar.alireza@gmail.com, m.aliasghari@gmail.com ).
H. Ghasemzadeh, A. Pourazar and M. Aliasghary
Iran


M.
Aliasgharyii
H. Ghasemzadeh, A. Pourazar and M. Aliasghary are with the Department of Electronic Engineering, urmia University, Urmia, Iran (email:
hadi.g.1384@gamil.com, pourazar.alireza@gmail.com, m.aliasghari@gmail.com ).
H. Ghasemzadeh, A. Pourazar and M. Aliasghary
Iran
Fuzzy controller
Rationalpowered membership function
CMOS
low power
[[1] M. Mottaghi Kashtiban, A. Khoei, and Kh. Hadidi; “Optimization of RationalPowered Membership Functions Using Extended Kalman Filter,” Journal of Fuzzy Sets and Systems (FSS), Elsevier, 159(23), 2007. ##[2] C. Y.Chen, Y. T. Hsieh and B. D. Liu; “Circuit implementation of linguistichedge fuzzy logic cotroller in currentmode” IEEE Transaction on Fuzzy Systems, Vol. 11, pp.624646, 2003. ##[3] M. Mottaghi Kashtiban, A. Khoei, and Kh. Hadidi; “A Currentmode, FirstOrder TakagiSugenoKang FLC, Supporting RationalPowered Membership Functions” IEICE TRANS. ELECTRON., Vol. E90C, No.6 2007. ##[4] R. Amirkhanzadeh, A. Khoei, Kh. Hadidi, “A mixedsignal currentmode fuzzy logic controller”, Int. Journal of Electronics and Communications, pp. 177184, 2005. ##[5] C. Dualibe, P. Jespers, and M. Verleysen; “A 5.26 MFLIPS programmable Analogue Fuzzy Logic Controller in a Standard CMOS 2.4μ Technology”, ISCAS, pp. 377380, May 2000. ##[6] Y.Chen, Y.Huang, D.Liu; “Currentmode defuzzifier circuit to realise the centroid strategy“, IEE Proc.Circuits Devices Syst., vol. 144, No. 5, Octobr 1997. ##[7] A. Naderi, A. Khoei, Kh. Hadidi, "High resolution RPMF using logarithmic and exponential approximation in CMOS technology," 16th International Conf. on Electrical Engineering, (ICEE) Tehran, Iran, 248 – 254, 2008. ##[8] A. j. Lopezmartin and A. Carlosena; “CurrentMode Multiplier/Divider Circuits Based on the MOS Translinear Principle,” Analog Integrated Circuits and Signal Processing, pp. 265278, 2001. ##[9] A. Naderi, A. Khoei, Kh. Hadidi; “A New High Speed and Low Power 4Quadrant CMOS Analog Multiplier in CurrentMode”, International Journal of Electronics and Communications, Elsevier, Vol. 63, Issue 9, 2009.##]