2010
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Scheduling SingleLoad and MultiLoad AGVs in Container Terminals
Scheduling SingleLoad and MultiLoad AGVs in Container Terminals
2
2
In this paper, three solutions for scheduling problem of the SingleLoad and MultiLoad Automated Guided Vehicles (AGVs) in Container Terminals are proposed. The problem is formulated as Constraint Satisfaction and Optimization. When capacity of the vehicles is one container, the problem is a minimum cost flow model. This model is solved by the highest performance Algorithm, i.e. Network Simplex Algorithm (NSA). If the capacity of the AGVs increases, the problem is a NPhard problem. This problem has a huge search space and is tackled by the Simulated Annealing Method (SAM). Three approaches for its initial solution and a neighborhood function to the search method are implemented. The third solution is a hybrid of SAM and NSA. This hybrid is applied to the Heterogeneous AGVs scheduling problem in container terminals. Several the same random problems are generated, solved by SAM with the proposed approaches and the simulation results are compared. The experimental results show that NSA provides a good initial solution for SAM when the capacity of AGVs is heterogeneous.
1
In this paper, three solutions for scheduling problem of the SingleLoad and MultiLoad Automated Guided Vehicles (AGVs) in Container Terminals are proposed. The problem is formulated as Constraint Satisfaction and Optimization. When capacity of the vehicles is one container, the problem is a minimum cost flow model. This model is solved by the highest performance Algorithm, i.e. Network Simplex Algorithm (NSA). If the capacity of the AGVs increases, the problem is a NPhard problem. This problem has a huge search space and is tackled by the Simulated Annealing Method (SAM). Three approaches for its initial solution and a neighborhood function to the search method are implemented. The third solution is a hybrid of SAM and NSA. This hybrid is applied to the Heterogeneous AGVs scheduling problem in container terminals. Several the same random problems are generated, solved by SAM with the proposed approaches and the simulation results are compared. The experimental results show that NSA provides a good initial solution for SAM when the capacity of AGVs is heterogeneous.
1
10


Hassan
Rashidii
Iran
Simulated Annealing Method
Network Simplex Algorithm
Optimization methods
Container Terminals
[Periodicals: ##[1] E.P.K Tsang, “Scheduling techniques  a comparative study”, British Telecom Technology Journal, Volume 13 (1), pp 1628, Martlesham Heath, Ipswich, UK, 1995. ##[2] B.J Wook and K.K Hwan,”A pooled dispatching strategy for automated guided vehicles in port container terminals”, International Journal of management science, Vol 6 (2), pp 4760, 2000. ##[3] Chiang, WenChyuan and A.R Robert, “Simulated Annealing Metaheuristic for the Vehicle Routing Problem with Time Windows,” Annals of Operations Research, Vol. 63, pp 327, 1996. ##[4] M.D. Grigoriadis, ”An Efficient Implementation of the Network Simplex Method”, Mathematical Programming Study Vol. 26, pp 83111, 1986. ##[5] M Grunow, H.O Günther and M Lehmann, “Dispatching multiload AGVs in highly automated seaport container terminals”, OR Spectrum, Volume 26 (2), pp 211235, 2004. ##[6] K.G.Murty, L.Jiyin, W YatWah, C,Zhang C.L Maria, J. Tsang and L..Richard, “DSS (Decision Support System) for operations in a container terminal”. Decision Support System, Vol 39, pp 309332., 2002. ##[7] R.K.Ahuja, T.L.Magnanti and J.B.Orlin, “Network Flows: Theory, Algorithms and Applications”. Prentice Hall, 1993. ##Technical Reports: ##[8] Z.Czech and P Czarnas, “Parallel Simulated Annealing for the Vehicle Routing Problem with Time Windows. In Proceedings of 10th Euromicto Workshop on Parallel Distributed and NetworkBased Processing, Canary Islands, Spain, pp 376383, 2002. ##[9] Y.Huang and W.J.Hsu, “Two Equivalent Integer Programming Models for Dispatching Vehicles at a Container Terminal”. CAIS, Technical Report 639798, School of Computer Engineering, Nan yang Technological University, Singapore, 2002. ##[10] H.Sen, “Dynamic AGVContainer Job Deployment”. Technical Report, HPCES Programme, SingaporeMIT Alliance, 2001. ##[11] M.Galati, H.Geng, and T.Wu, “A Heuristic Approach For The Vehicle Routing Problem Using Simulated Annealing”, Lehigh University, Technical Report IE316, 1998. ##[12] Y. Cheng, H. Sen, K. Natarajan, T. Ceo, and K.Tan,"Dispatching automated guided vehicles in a container terminal", Technical Report, National University of Singapore, 2003. ##Papers from Conference Proceedings (Published): ##[13] S.H Chan, “Dynamic AGVContainer Job Deployment”, Master of Science, University of Singapore, 2001. ##[14] H. Rashidi and E.P.K Tsang, "Applying the Extended Network Simplex Algorithm and a Greedy Search Method to Automated Guided Vehicle Scheduling", in Proceedings 2005, the 2nd Multidisciplinary International Conference on Scheduling: Theory & Applications (MISTA), New York, Vol 2, pp 677693. ##[15] T. Hasama, H. Kokubugata and H. Kawashima, “A Heuristic Approach Based on the String Model to Solve Vehicle Routing Problem with Backhauls”, Proceeding of the 5th World Congress on Intelligent Transport Systems (ITS), Seoul, 1998. ##[16] J.M. Patrick and P.M. Wagelmans, “Dynamic scheduling of handling equipment at automated container terminals”, Technical Report EI 200133, Erasmus University of Rotterdam, Econometric Institute, 2001. ##[17] J.M. Patrick and P.M. Wagelmans, “Effective algorithms for integrated scheduling of handling equipment at automated container terminals”, Technical Report EI 200119, Erasmus University of Rotterdam, Econometric Institute, 2001. ##[18] L. Qiu, W.J. Hsu, S.Y. Huang and H. Wang (2002), “Scheduling and Routing Algorithms for AGVs: a Survey”. International Journal of Production Research, Taylor & Francis Ltd, Vol. 40 (3), pp 745760. ##[19] L. Qiu, and W.J Hsu, “A bidirectional path layout for conflictfree routing of AGVs”. International Journal of Production Research, Volume 39 (10), pp 21772195, 2001. ##[20] L. Qiu and W.J. Hsu, “Scheduling of AGVs in a meshlike path topology”. Technical Report CAISTR0134, Centre for Advanced Information Systems, School of Computer Engineering, Nanyang Technological University, Singapore, 2001. ##[21] J. Böse, T. Reiners, D. Steenken, and S. Voß, ”Vehicle Dispatching at Seaport Container Terminals Using Evolutionary Algorithms”. Proceedings of the 33rd Annual Hawaii International Conference on System Sciences, IEEE, pp 110, 2000. ##Dissertations: ##[22] H. Rashidi, “Dynamic Scheduling of Automated Guided Vehicles in Container Terminals”, PhD Thesis, Department of Computer Science, University of Essex, 2006. ##[23] D.J Kelly. and G.M. ONeill, "The Minimum Cost Flow Problem and The Network Simplex Solution Method", Master Degree Dissertation, University College, Dublin, 1993. ##[24] C. Y Leong, "Simulation study of dynamic AGVcontainer job deployment scheme", Master of science, National University of Singapore, 2001 ##[25] A. Larsen, “The Dynamic Vehicle Routing Problem”, PhD Thesis, Technical University of Denmark, 2000.##]
Small Scale Effect on the Buckling Analysis of a DoubleWalled Carbon Nanotube under External Radial Pressure Using Energy Method
Small Scale Effect on the Buckling Analysis of a DoubleWalled Carbon Nanotube under External Radial Pressure Using Energy Method
2
2
In this paper, using energy method, small scale effects on the buckling analysis of a doublewalled carbon nanotube (DWCNT) under external radial pressure is studied. The constitutive equations derived for a DWCNT using the nonlocal theory of elasticity which Eringen are presented for the first time. By minimizing the second variation of the total energy for a DWCNT, hence, the value of the nonlocal critical buckling load is obtained. It is seen from the results that the nonlocal critical buckling load increases with increasing the circumferential wave number. Moreover, it is seen that the nonlocal critical buckling load is lower than that of the local one. It is shown from the results that the ratio of the critical buckling load decreases with increasing the length of nanotubes while it increases with decreasing the radius of the outer tube.
1
In this paper, using energy method, small scale effects on the buckling analysis of a doublewalled carbon nanotube (DWCNT) under external radial pressure is studied. The constitutive equations derived for a DWCNT using the nonlocal theory of elasticity which Eringen are presented for the first time. By minimizing the second variation of the total energy for a DWCNT, hence, the value of the nonlocal critical buckling load is obtained. It is seen from the results that the nonlocal critical buckling load increases with increasing the circumferential wave number. Moreover, it is seen that the nonlocal critical buckling load is lower than that of the local one. It is shown from the results that the ratio of the critical buckling load decreases with increasing the length of nanotubes while it increases with decreasing the radius of the outer tube.
11
16


Z. S.
Mousavi i
Iran


A.
Ghorbanpour Arani
Iran


M.
Mohammadimehr
Iran
Nonlocal shell model
Buckling
DWCNT
External radial pressure
Energy method
[[1] P. Ball, "Roll up for the revolution", Nature, vol. 414, pp. 142144, 2001. ##[2] C. Q. Ru, “Axially compressed buckling of a double walled carbon Nanotube embedded in an elastic medium", Journal of the Mechanics and Physics of Solids, vol. 49, pp. 12651279, 2001. ##[3] C. Y. Wnag, C. Q. Ru ,A. Mioduchowski, “Axially compressed buckling of pressured multiwall carbon Nanotube”, International Journal of Solids and Structures, vol. 40, pp. 38933911, 2003. ##[4] X. Guo, A. Y. T. Leung, X. Q. Jiang, Y. Huang, “”, Composite, vol. 39 (part B), pp. 202208, 2008. ##[5] H. L. Ball, W. J. Chang, "A closedform solution for critical buckling temperature of a singlewalled carbon Nanotube", Physica E, vol. 41, pp. 14921494, 2009. ##[6] A. Ghorbanpour Arani, R. Rahmani, A. Arefmanesh, and S. Golabi, ”Buckling analysis of multiwalled carbon nanotubes under combined loading considering the effect of small length scale”, Journal of Mechanical Science and Technology, vol. 22, pp. 429439, 2008. ##[7] A.R. Ranjbartoreh, A. Ghorbanpour, and B. Soltani, ”Doublewalled carbon nanotube with surrounding elastic medium under axial pressure”. Physica E, vol. 39, pp. 230239, 2007. ##[8] A. C. Eringen,”On differential equations of nonlocal elasticity and solutions of screw dislocation and surface waves”, Journal of Applied Physics, vol. 54, pp.47034710, 1983. ##]
Buckling of Laminates with Multiple ThroughtheWidth Delaminations Using Spring Simulation Model
Buckling of Laminates with Multiple ThroughtheWidth Delaminations Using Spring Simulation Model
2
2
Delamination is one of the most common failure modes in composite structures. In particular, when the laminated composites are subjected to compressive loads, delamination becomes a constraint in the design process. In this study, the system is modeled as a plate supported by an elastic foundation. The elastic adhesive layer between the buckled sublaminates is represented by some parallel springs. The plate on a discontinuous foundation is treated as a continuous foundation but with added transverse forces at a number of discrete points in the delamination regions to make the net transverse force at each of these points to vanish. The delaminated plates which are analyzed in this study contain one or two throughthewidth delaminations.Also, an extensive finite element analysis is performed by using ANSYS5.4 general purpose commercial software, and the results are compared with those obtained by the analytical model. The agreement between the results is very good.
1
Delamination is one of the most common failure modes in composite structures. In particular, when the laminated composites are subjected to compressive loads, delamination becomes a constraint in the design process. In this study, the system is modeled as a plate supported by an elastic foundation. The elastic adhesive layer between the buckled sublaminates is represented by some parallel springs. The plate on a discontinuous foundation is treated as a continuous foundation but with added transverse forces at a number of discrete points in the delamination regions to make the net transverse force at each of these points to vanish. The delaminated plates which are analyzed in this study contain one or two throughthewidth delaminations.Also, an extensive finite element analysis is performed by using ANSYS5.4 general purpose commercial software, and the results are compared with those obtained by the analytical model. The agreement between the results is very good.
17
24


M.
Kharazi
Iran


H. R
. Ovesyii
Iran
delamination
Buckling
Composite laminates
Spring Simulation
[[1] H. Chai, C. D. Babcock, and W. G. Knauss, "One dimensional modeling of failure in laminated plates by delamination buckling," International Journal of Solids and Structures, Vol. 17, pp 10691083, 1981. ##[2] W. J. Bottega, and A. Maewal, "Delamination buckling and growth in laminates," Journal Applied Mechanics, Vol. 50, pp 184189, 1983. ##[3] K. N. Shivakumar, and J. D Withcomb, "Buckling of sublaminate in a quasi isotropic composite laminates," Journal of Composite Materials, Vol. 19, pp 218, 1985. ##[4] J. S. Anastasiadis, and G. J. Simitses, "Spring simulated delamination of axially loaded flat laminates," Composite Structures, Vol. 17, pp 6785, 1991. ##[5] B. D. Davidson, "Delamination buckling: theory and experiment," Journal of Composite Materials, Vol. 25, pp 13511378, 1991. ##[6] C. H. Piao, "Shear deformation theory of compressive delamination buckling and growth," AIAA Journal, Vol. 29, No. 5, pp 813819, 1991. ##[7] H. Suemasu, "Compressive behavior of fiber reinforced composite plates with a center delamination," Adv. Composite Materials, Vol. 1, No. 1, pp 2337, 1991. ##[8] H. Suemasu, "Effects of multiple delaminations on compressive buckling behaviors of composite panels," Journal of Composite Materials, Vol. 27, No. 12, pp 11721192, 1993. ##[9] M. Adan, I. Sheinman, and E. Altus, "Buckling of multiply delaminated beams," Journal of Composite Materials, Vol. 28, No. 1, pp 7790, 1994. ##[10] J. T. S. Wang, and S. H. Cheng, "Local buckling of delaminated beams and plates using continuous analysis," Journal of Composite Materials, Vol. 29, No. 10, pp 13741402, 1995. ##[11] J. T. S. Wang, and J. T. Huang, "Strain energy release rate of delaminated composite plates using continuous analysis," Journal of Composites Engineering, Vol. 7, pp 731744, 1994. ##[12] K. W. Shahwan, and A. M. Wass, "A mechanical model for the buckling of unilaterally constrained rectangular plates," International Journal of Solids and Structures, Vol. 31, No. 1, pp 7587, 1994. ##[13] D. W. Sleight, and J. T. Wang, "Buckling analysis of debonded sandwich panel under compression," NACA Technical Memorandum, 1995. ##[14] D. Shu, "Buckling of multiple delaminated beams”, International Journal of Solids and Structures," Vol. 25, No. 13, pp 14511465, 1998. ##[15] N. G. Andrews, R. Massabo, and B. N. Cox, "Elastic interaction of multiple delaminations in plates subject to cylindrical bending," International Journal of Solids and Structures, Vol. 43, pp 855886, 2006. ##[16] H. R. Ovesy, H. Hosseinitoudeshky, and M. Kharazi, "Buckling analysis of laminates with multiple throughthewidth delaminations by using Spring simulated model," in Proc. of III European Conference on Computational Mechanics Solids, Structures and Coupled Problems in Engineering, Lisbon, Portugal, 58 June 2006, (Published by Springer – Netherlands). ##[17] M. Kharazi, H. R. Ovesy, and S. A. M. GhannadPour, "The buckling analysis of delaminated composite plates including the effects of b bendtwist coupling by using spring simulation technique," in Proc. of the 8th International Conference on Computational Structures Technology, Gran Canaria, Spain, 1215 Sep 2006, (Published by CivilComp Press – Scotland). ##[18] M. Kharazi, and H. R. Ovesy, "Postbuckling behavior of composite plates with troughthewidth delaminations," in Proc. of the ThinWalled Structure Conference,, University of Strathclyde, Glasgow, UK, 2627 June 2007. ##[19] J. M. Whitney, Structural analysis of laminated anisotropic plates, Technomic Publishing Company. Ink 1987. ##[20] F. Bloom, and D. Coffin, Handbook of thin plate buckling and postbuckling, Chapman & Hall/CRC 2001. ##]
Study on Experimental and Modeling of Rotary Roll Dressing of Grinding Wheels
Study on Experimental and Modeling of Rotary Roll Dressing of Grinding Wheels
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2
Two of the important parameters in grinding operation are surface roughness of the workpiece and the amount of consumed energy. These parameters are strongly affected by the condition of grinding wheel surface which is dependent on the dressing parameters. Predicting the roughness of the grinding wheel surface after dressing with known dressing parameters can improve the grinding process. Researchers have presented several models of the grinding surface after dressing. In this article, these models are analyzed and an improved model along with computer simulation of grinding wheel surface is presented with regard to rotary dressing parameters. Finally, the model is verified with experimental results. The theoretical values reasonably compare with experimental results. On the basis of this model and experimental results the effect of different rotary roll dressing parameters on grinding wheel and workpiece surface roughness are discussed.
1
Two of the important parameters in grinding operation are surface roughness of the workpiece and the amount of consumed energy. These parameters are strongly affected by the condition of grinding wheel surface which is dependent on the dressing parameters. Predicting the roughness of the grinding wheel surface after dressing with known dressing parameters can improve the grinding process. Researchers have presented several models of the grinding surface after dressing. In this article, these models are analyzed and an improved model along with computer simulation of grinding wheel surface is presented with regard to rotary dressing parameters. Finally, the model is verified with experimental results. The theoretical values reasonably compare with experimental results. On the basis of this model and experimental results the effect of different rotary roll dressing parameters on grinding wheel and workpiece surface roughness are discussed.
25
32


A. H.
Azizii
Iran


S. M.
Rezaei
Iran


A.R.
Rahimi
Iran


H.
Baseri
Iran
Rotary dressing
Dressing parameters
Roughness
Steady profile
[[1] J. Verkerk, ”The effect of wheel dressing on wheelwear ,work surface roughness and surface integrity,” SME ,Int. Eng. Con. ,may 1977, p276283. ##[2] S. Malkin, T. Murray, “Mechanics of rotary dressing of grinding wheels,” ASME, 1977, p95. ##[3] S. Malkin, T. Murray, “ Effect of rotary dressing on grinding wheels performance,” ASME ,V.100 ,1978, p297303 ##[4] E. Brinksmeier, M. Cinar, "Characterization of Dressing Processes by Determination of the Collision Number of the Abrasive Grits," Annals of the ClRP Vol. 44, 1995,p299304. ##[5] Z. Pruzak, J. A. Webster, I. D. Marinescu, "Influence of dressing parameters on grinding performance of CBN/Seeded gel hybrid wheels in cylindrical grinding," Int. Jou. Production Research, 1997, Vol.35: P2899– 2915 ##[6] H. Baseri, S. M. Rezaei, A. R. Rahimi, M. Rezaeian, "Modeling of Disc Dressing Forces," Machining Science and Technology, Vol. 11, N. 2, April/June 2007,p201216 ##[7] H. Baseri, S. M. Rezaei, A. R. Rahimi, M. Saadat, "Analysis of the disc dressing effects on grinding performance PART 1: Simulation of the disc dressed wheel surface," Machining Science and Technology, Vol. 11, N. 2, April/June 2007,p183196. ##[8] H. Baseri, S. M. Rezaei, A. R. Rahimi, M. Saadat, "Analysis of the disc dressing effects on grinding performance PART 2: Effects of the wheel topographical parameters on the specific energy and workpiece surface roughness," Machining Science and Technology, Vol. 11, N. 2, April/June 2007,p197213.##]
Molecular Dynamics Simulation of Al Energetic Nano Cluster Impact (ECI) onto the Surface
Molecular Dynamics Simulation of Al Energetic Nano Cluster Impact (ECI) onto the Surface
2
2
On the atomic scale, Molecular Dynamic (MD) Simulation of Nano Al cluster impact on Al (100) substrate surface has been carried out for energies of 120 eV/atom to understand quantitatively the interaction mechanisms between the cluster atoms and the substrate atoms. The many body Embedded Atom Method (EAM) was used in this simulation. We investigated the maximum substrate temperature Tmax and the time tmax within which this temperature is reached as a function of cluster sizes. The temperature Tmax is linearly proportional to both energy per atom and total cluster energy. For the constant energy per atom and the cluster size increase, the correlated collisions rapidly transferred energy to the substrate, and the time tmax approached a constant value. We investigated the temperature Tmax dependence on the total energy ET and the cluster size. We showed that the cluster implantation and sputtering atoms from the surface are affected by the cluster size and kinetic energy of the clusters. Finally, time dependence of the number Ndis of disordered atoms in the substrate was observed.
1
On the atomic scale, Molecular Dynamic (MD) Simulation of Nano Al cluster impact on Al (100) substrate surface has been carried out for energies of 120 eV/atom to understand quantitatively the interaction mechanisms between the cluster atoms and the substrate atoms. The many body Embedded Atom Method (EAM) was used in this simulation. We investigated the maximum substrate temperature Tmax and the time tmax within which this temperature is reached as a function of cluster sizes. The temperature Tmax is linearly proportional to both energy per atom and total cluster energy. For the constant energy per atom and the cluster size increase, the correlated collisions rapidly transferred energy to the substrate, and the time tmax approached a constant value. We investigated the temperature Tmax dependence on the total energy ET and the cluster size. We showed that the cluster implantation and sputtering atoms from the surface are affected by the cluster size and kinetic energy of the clusters. Finally, time dependence of the number Ndis of disordered atoms in the substrate was observed.
33
36


K.
Mirabbaszadehi
Iran


P.
Nayebiii
Iran


S.
Saramad
Iran


E.
Zaminpayma
Iran
Molecular Dynamic Simulation
Embedded Atom Method potential
Nanocluster
Al
Thin Film
Disordered Atoms
Implantation Atoms
Sputtering Atoms
[[1] Haberland, H.; Mall, M.; Moseler, M.; Qiang, Y.; Reiners, Y. Th. ; Thurner, Y. Filling of micronsized contact holes with copper by energetic cluster impact, J. Vac. Sci. and Technol. 1994, A12, 29252930 ##[2] Yamada, I.; Taksoka, H. Low temperature epitaxy by ionizedcluster beam, J.Vac.Sci.Technol. 1986, A 4, 722727 ##[3] Beuhler, R.J.; Friedlander, G. Clusterimpact fusion, Phys. Rev. Lett. 1989, 63, 1292  1295 ##[4] Echenique, P.M.; Manson, J.R. Clusterimpact fusion, Phys. Rev. Lett. 1990, 64, 1413  1416 ##[5] Yamada, I.; Takaoka, G.H. Ionized Cluster Beams, Physics and Technology, Jpn. I. Appl. Phys. 1993, 32, 21212124. ##[6] I. Yamada, H. Inokawa and T. Takagi, .I. Appl. Phys. 1984, 56, 27642782 ##[7] Tagaki, T. Ionized Cluster Beam Deposition, 1988 Noyes, New Jersey,chap.5,p.106 ##[8] I. Yamada, G.H. Takaoka, Xray characteristics of atomically flat gold films deposited by ICB, Nucl. Instr. and Meth. B, 1991, 59/60, 216218. ##[9] M. Adachi, S. Ikuni, K. Yamada, Optical Characteristics of HighPower Excimer Laser Mirrors of SingleCrystal Aluminum Film With High Reflectance and Durability ,Nucl. Instr. and Meth. B, 1991, 59/60 , 940 ##[10] C. Cleveland and U. Landman, Dynamics of ClusterSurface Collisions ,Science, 1992, 257, 355361 ##[11] H. Haberland , Zinetulla Insepov , Michael Moseler, Moleculardynamics simulation of thinfilm growth by energetic cluster impact , Phys. Rev. B, 1995,51, 1106111067 ##[12] R.S. Averback and Mai Chaly. Sputtering of nanoparticles: Molecular dynamics study of Au impact on 20 nm sized Au nanoparticles, Nucl. Instr. and Meth. B , 1994,90, 191194. ##[13] C. Anders, S. Meblinger, H.M. Urbassek, Deformation of slow liquid and solid clusters upon deposition: A moleculardynamics study of Al cluster impact on an Al surface, Surface Science , 2006, 600,2587–2593 ##[14] K.H. MeiwesBroer, Metal Clusters at Surfaces: Structure, Quantum Properties, Physical Chemistry, 2000, Springer Series in Cluster Physics, Springer, Berlin. ##[15] C. Binns, Nanoclusters deposited on surfaces ,Surf. Sci. Rep., 2001, 44, 149. ##[16] Y. Xia, N.J. Halas , Shapecontrolled synthesis and surface plasmonic properties of metallic nanostructures, MRS Bull., 2005, vol. 30 ,5 ##[17] S. Pratontep, P. Preece, C. Xirouchaki, R.E. Palmer, C.F. Sanz Navarro, S.D. Kenny, R. Smith, Scaling Relations for Implantation of SizeSelected Au, Ag, and Si Clusters into Graphite, Phys. Rev. Lett. , 2003,90, 055503055507. ##[18] R. Smith, C. Nock, S. Kenny, J.J. Belbruno, M. Di Vece, S. Palomba, R.E. Palmer, Modeling the pinning of Au and Al clusters on graphite,Phys. Rev. B , 2006,73 , 125429125434. ##[19] K. Meinander, K. Nordlund, J. Keinonen, Size dependent epitaxial cluster deposition: The effect of deposition energy, Nucl. Instrum. Meth. B, 2006, 242, 161163 ##[20] S. M. Foiles, M. I. Baskes, and M. S. Daw, Embeddedatommethod functions for the fcc metals Cu, Ag, Au, Ni, Pd, Pt, and their alloys, Phys. Rev. B , 1986,33 , 78937991 ##[21] Daw, Baskes, Semiempirical, Quantum Mechanical Calculation of Hydrogen Embrittlement in Metals,Phys Rev Lett, 50, 1983,12851288Periodicals: ##]
Design and Construction of a New Capacitive Tactile Sensor for Measuring Normal Tactile Force
Design and Construction of a New Capacitive Tactile Sensor for Measuring Normal Tactile Force
2
2
This paper presents the design, construction and testing of a new capacitive tactile sensor for measurement of normal tactile force. The operation of proposed sensor has been investigated in ASTABLE and MONOSTABLE circuits. According to the results of these circuits the deviation of ASTABLE circuit results is less than MONOSTABLE circuit results. In addition, the results obtained from ASTABLE circuit are less separable compared to those of MONOSTABLE circuit. Remarkable advantages of this circuit are its simplicity and low energy consumption aside from its ability to be miniaturized which makes it a good substitute for the sensor in robotics and medical sciences such as minimally invasive surgery (MIS).
1
This paper presents the design, construction and testing of a new capacitive tactile sensor for measurement of normal tactile force. The operation of proposed sensor has been investigated in ASTABLE and MONOSTABLE circuits. According to the results of these circuits the deviation of ASTABLE circuit results is less than MONOSTABLE circuit results. In addition, the results obtained from ASTABLE circuit are less separable compared to those of MONOSTABLE circuit. Remarkable advantages of this circuit are its simplicity and low energy consumption aside from its ability to be miniaturized which makes it a good substitute for the sensor in robotics and medical sciences such as minimally invasive surgery (MIS).
37
42


S.
Mosafer Khoorjestani
Iran


S.
Najarianii
Iran


A
. Tavakoli Golpayganiiii
Iran


H.
Sherkativ
Iran
Tactile Sensor
Capacitive Sensor
Tactile Force
[[1] P. Dario, "Tactile SensingTechnology and Applications," Sensors and Actuators Journal, pp. 251261, 1991. ##[2] B.J. Kane, M.R. Cutkosky, and G.T. Kovacs, "compatible traction stress sensor for use in highresolution tactile imaging," Sensors and Actuators Journal, pp. 916, 1996. ##[3] H.R. Nicholls, and M.H. Lee, "A survey of robot tactile sensing technology," Robotics Research Journal, pp. 330, 1989. ##[4] J. Dargahi, and S. Najarian, "Advances in Tactile Sensors Design/Manufacturing and its Impact on Robotics Applications – A Review," Industrial Robot Journal, pp. 268281, 2005. ##[5] J. Dargahi, and S. Najarian, "Human Tactile Perception as A Standard for Artificial Tactile Sensing  A Review," International Journal of Medical Robotics and Computer Assisted Surgery, pp. 2335, 2004. ##[6] M.H. Lee, and H.R. Nicholls, "Tactile Sensing for Mechatronics a State of the Art Survey," Mechatronics, pp. 131, 1999. ##[7] M.H. Lee, "Tactile Sensing: New Directions, New Challenges," International Journal of Robotics Research, pp. 636643, 2000. ##[8] R.A. Russell, "Robot Tactile Sensing," Prentice Hall, pp. 515, 1990. ##[9] J.S. Wilson, "Sensor Technology Handbook," Elsevier, Newnes, pp. 315330, 2005. ##[10] T. Mei, W.J. Li, Y. Ge, Y. Chen, L. Ni, and M.H. Chan, "An Integrate MEMS Three Dimensional Tactile Sensor with Large Force Range," Sensors and Actuators Journal, pp. 155162, 2000. ##[11] P.H. Chappell, and J.E. Elliott, "Contact Force Sensor for Artificial Hands with a Digital Interface for a Controller," Measurement Science and Technology, pp. 12751279, 2003. ##[12] J. Dargahi, and S. Najarian, "An Endoscopic Force Position Grasper with Minimum Sensors," Canadian Journal of Electrical and Computer Engineering, pp. 155161, 2004. ##[13] J. Dargahi, "An Endoscopic and Robotic Tooth like Compliance and Roughness tactile sensor," Journal of Mechanical Design, pp. 576582, 2002. ##[14] J. Fraden, "Handbook of Modern Sensors," Springer Verlag, pp.147, 2003. ##[15] K. Suzuki, "High density tactile sensor arrays," Advanced Robotics, pp. 283287, 1993. ##[16] B. Preising, T.C. Hsia, and B. Mittelsradt, "A literature review: robots in medicine," IEEE Journal, pp. 1322, 1991. ##[17] E.S. Kolesar, and C.G. Dyson, "Piezoelectric tactile integrated circuit sensor," pp.10011007, 1995. ##[18] K. Larry, "Capacitive Sensors," IEEE Press, Piscataway N.J., pp. 1217, 1997. ##[19] R.D. Howe, "Tactile Sensing and control of Robotics Manipulation," Tactile Sensors for Robotics and Medicine, pp 245261, 1994. ##[20] B. Nowicki, and A. Jarkiewicz, "The inprocess surface roughness measurement using FFC method," International Journal Machine Tools and Manufacture, pp. 725732, 1998.##]
A New Highorder TakagiSugeno Fuzzy Model Based on Deformed Linear Models
A New Highorder TakagiSugeno Fuzzy Model Based on Deformed Linear Models
2
2
Amongst possible choices for identifying complicated processes for prediction, simulation, and approximation applications, highorder TakagiSugeno (TS) fuzzy models are fitting tools. Although they can construct models with rather high complexity, they are not as interpretable as firstorder TS fuzzy models. In this paper, we first propose to use Deformed Linear Models (DLMs) in consequence parts of a TS fuzzy model, which provides both complexity and interpretability. We then prove that in order to minimize considered error indices, linear and nonlinear parts of DLMs can be optimized independently. A localization of DLMs in inputspace of the TS fuzzy model is done using an appropriate sigmoidbased membership function, which can represent a fuzzy subspace with enough smoothness and flat top. An incremental algorithm is also proposed to identify the suggested fuzzy model. Then, through an illustrative example, the formation of DLMs to approximate a nonlinear function is demonstrated. The applicability and effectiveness of the introduced fuzzy modeling approach is examined in three case studies: prediction of a chaotic time series, identification of a steam generator model, and approximation of a nonlinear function for a sun sensor. The obtained results demonstrate the higher accuracy and better generalization of our modeling approach as compared with those of some other wellknown stateoftheart approaches.
1
Amongst possible choices for identifying complicated processes for prediction, simulation, and approximation applications, highorder TakagiSugeno (TS) fuzzy models are fitting tools. Although they can construct models with rather high complexity, they are not as interpretable as firstorder TS fuzzy models. In this paper, we first propose to use Deformed Linear Models (DLMs) in consequence parts of a TS fuzzy model, which provides both complexity and interpretability. We then prove that in order to minimize considered error indices, linear and nonlinear parts of DLMs can be optimized independently. A localization of DLMs in inputspace of the TS fuzzy model is done using an appropriate sigmoidbased membership function, which can represent a fuzzy subspace with enough smoothness and flat top. An incremental algorithm is also proposed to identify the suggested fuzzy model. Then, through an illustrative example, the formation of DLMs to approximate a nonlinear function is demonstrated. The applicability and effectiveness of the introduced fuzzy modeling approach is examined in three case studies: prediction of a chaotic time series, identification of a steam generator model, and approximation of a nonlinear function for a sun sensor. The obtained results demonstrate the higher accuracy and better generalization of our modeling approach as compared with those of some other wellknown stateoftheart approaches.
43
54


Ahmad
Kalhor
Iran
akalhor@ut.ac.ir


Babak N.
Araabi
Iran


Caro
Lucasi
Iran
Takagi Sugeno fuzzy model
Identification
deformed linear models
sigmoidbased membership function
prediction and approximation
[[1] T. Takagi, and M. Sugeno, "Fuzzy identification of systems and its applications to modeling and control," IEEE Trans. Syst., Man Cybern., vol. 15, pp. 116132, 1985. ##[2] R. Jang, "ANFIS: Adaptive networkbased fuzzy inference system," IEEE Trans. Syst., Man, Cybern., vol. 23, pp. 665685, 1993. ##[3] N. Kasabov, "DENFIS: Dynamic Evolving NeuralFuzzy Inference System and its application for timeseries prediction," IEEE Trans. Fuzzy Syst., vol. 10, pp. 144154, 2002. ##[4] Y. Chen, B. Yang, A. Abraham, and L. Peng, "Automatic design of hierarchical Takagi–Sugeno type fuzzy systems using evolutionary algorithms," IEEE Trans. Fuzzy Syst., vol. 15, pp. 385397, 2007. ##[5] J. Abonyi, R. Babuska, and F. Szeifert, "Modified GathGeva fuzzy clustering for identification of TakagiSugeno fuzzy models," IEEE Trans. Syst. Man and Cybern.—PART B, vol. 32, pp. 612621, 2002. ##[6] P. Pulkkinen, and H. Koivisto, "Identification of interpretable and accurate fuzzy classifiersand function estimators with hybrid methods," Applied Soft Computing, vol. 7, pp. 520533, 2007. ##[7] C. F. Juang, "A selforganizing TStype fuzzy network with support vector learning and its application to classification problems," IEEE Trans. Fuzzy Syst., vol. 15, pp. 9981008, 2007. ##[8] A. Kalhor, B. N. Araabi, and C. Lucas, "Online identification of a neurofuzzy model through indirect fuzzy clustering of data space," FUZZIEEE2009, the 18th Int. conference on fuzzy systems, 2124 Aug., Korea, 2009, pp. 356359. ##[9] C. Li, J. Zhou, X. Xiang, Q. Li and X. An, "T–S fuzzy model identification based on a novel fuzzy cregression model clustering algorithm," Engineering Applications of Artificial Intelligence, vol. 22, pp. 646–653, 2009. ##[10] C .F. Juang, "A TSKType recurrent fuzzy network for dynamic systems processing by neural network and genetic algorithms," IEEE Trans. Fuzzy Syst., vol. 10, pp. 155170, 2008. ##[11] H. Du, and N. Zhang, "Application of evolving Takagi–Sugeno fuzzy model to nonlinear system identification," Applied soft computing, vol. 8, pp. 876686, 2007. ##[12] L. Zhaoa , F. Qiana, Y. Yangb, Y. Zengb, and H. Sub, "Automatically extracting T–S fuzzy models using cooperative random learning particle swarm optimization," Applied Soft Computing , vol. 10, pp. 938944, 2010. ##[13] P.A. Mastorocostas, and J.B. Theocharis, "A recurrent fuzzyneural model for dynamic system identification," IEEE Trans. Syst. Man Cybern., vol. 32, pp. 176190, 2002. ##[14] C. Li, and K. H. Cheng, " Recurrent neurofuzzy hybridlearning approach to accurate system modelin," Fuzzy Sets and Systems, vol. 58, pp. 194122, 2007. ##[15] A. Savran, "An adaptive recurrent fuzzy system for nonlinear identification," Applied Soft Computing,vol. 7, pp. 593600, 2007. ##[16] O. Nelles, Nonlinear System Identification, New York: Springer, 2001, p. 365. ##[17] A. Kalhor, B.N. Araabi, and C. Lucas, "A New Split and Merge Algorithm for Structure Identification in TakagiSugeno Fuzzy Model," in Proc. of 7th Int. Conf. on Intelligent Systems Design and Applications, 2007, pp. 258261. ##[18] A. Kalhor, B.N. Araabi, and C. Lucas, "An Online Predictor Model as Adaptive Habitually Linear and Transiently Nonlinear Model," Evolving Systems, vol. 1, pp. 2941, 2010. ##[19] B. Rezaee, and M.H.F. Zarandi, "Datadriven fuzzy modeling for Takagi–Sugeno–Kang fuzzy system," Information Sciences, vol. 180, pp. 241255, 2010. ##[20] J.B. Theocharis, "A highorder recurrent neurofuzzy system with internal dynamics: Application to the adaptive noise cancellation," Fuzzy Sets and Systems, vol. 157, pp. 471500, 2006. ##[21] Z.L. Sun, K. F. Au, and T. M. Choi, "A neurofuzzy inference system through integration of fuzzy logic and extreme learning machines," IEEE Trans. Syst. Man Cybern.—PART B, vol. 37, pp. 13211331, 2007. ##[22] J. N. Choi, S. K. Oh and W. Pedrycz, "Identification of fuzzy models using a successive tuning method with a variant identification ratio," Fuzzy Sets and Systems, vol. 159, pp. 28732889, 2008. ##[23] K. B. Petersen, and M. S. Pedersen, "The matrix cookbook," Available: http://matrixcookbook.com, Version: Nov. 14, 2008. ##[24] De Moor B.L.R. (ed.) , "DaISy: Database for the Identification of Systems," Department of Electrical Engineering, ESAT/SISTA, K.U.Leuven, Belgium, Available: http://www.esat.kuleuven.ac.be/sista/daisy.##]
An ANOVA Based Analytical Dynamic Matrix Controller Tuning Procedure for FOPDT Models
An ANOVA Based Analytical Dynamic Matrix Controller Tuning Procedure for FOPDT Models
2
2
Dynamic Matrix Control (DMC) is a widely used model predictive controller (MPC) in industrial plants. The successful implementation of DMC in practical applications requires a proper tuning of the controller. The available tuning procedures are mainly based on experience and empirical results. This paper develops an analytical tool for DMC tuning. It is based on the application of Analysis of Variance (ANOVA) and nonlinear regression analysis for First Order plus Dead Time (FOPDT) process models. It leads to a simple formula which involves the model parameters. The proposed method is validated via simulations as well as experimental results. A nonlinear pH neutralization model is used for the simulation studied. It is further implemented on a laboratory scale control level plant. A robustness analysis is performed based on the simulation results. Finally, comparison results are provided to show the effectiveness of the proposed methodology.
1
Dynamic Matrix Control (DMC) is a widely used model predictive controller (MPC) in industrial plants. The successful implementation of DMC in practical applications requires a proper tuning of the controller. The available tuning procedures are mainly based on experience and empirical results. This paper develops an analytical tool for DMC tuning. It is based on the application of Analysis of Variance (ANOVA) and nonlinear regression analysis for First Order plus Dead Time (FOPDT) process models. It leads to a simple formula which involves the model parameters. The proposed method is validated via simulations as well as experimental results. A nonlinear pH neutralization model is used for the simulation studied. It is further implemented on a laboratory scale control level plant. A robustness analysis is performed based on the simulation results. Finally, comparison results are provided to show the effectiveness of the proposed methodology.
55
64


Peyman
Bagheri
Iran


Ali
KhakiSedigh
Iran
Dynamic Matrix Control
Tuning
Analysis of Variance (ANOVA)
Nonlinear Regression
FOPDT
industrial processes
pH process
Level process
[[1] SJ. Qin and TA, Badgwell, "A survey of industrial model predictive control technology," Control engineering practice, vol. 11, pp. 733764, 2003. ##[2] C. R. Cutler and B. L. Ramaker, "Dynamic Matrix Control: A Computer Control Algorithm," Proceeding of Joint Automatic Control Conference, 1980. ##[3] E. F. Camacho and C. Bordons, Model Predictive Control, 2nd ed, Springer, 2005. ##[4] W. Wojsznis, J. Gudaz, T. Blevins and A. Mehta, "Practical approach to tuning MPC," ISA Transactions, vol. 42, pp. 149162, 2003. ##[5] E. Ali and A. G. Ashraf, "Online Tuning of Model Predictive Controllers Using Fuzzy Logic," The Canadian Journal of Chemical Engineering, vol. 81, pp. 111, Oct 2003. ##[6] A. Jiang and A. Jutan, "Response Surface Tuning Methods in Dynamic Matrix Control of a Pressure Tank System," Ind. Eng. Chem. Res., vol. 39, pp. 38353843, 2000. ##[7] A. R. Neshasteriz, A. Khaki Sedigh and H. Sadjadian, "Generalized predictive control and tuning of industrial processes with second order plus dead time models," Journal of Process Control, vol. 20, pp. 3672, Jan 2010. ##[8] R. Shridhar and D. J. Cooper, "A Tuning Strategy for Unconstrained SISO Model Predictive Control," Ind. Eng. Chem. Res, vol. 36, pp. 729746, 1997. ##[9] J. H. Lee, and Yu, Z.H, "Tuning of model predictive controllers for robust performance," Computer. Chem. Eng., vol. 18, pp. 15–37, 1994. ##[10] E. J. Iglesias, M. E, Sanjuán and C. A. Smith, "Tuning equation for dynamic matrix control in SISO loops," Ingeniería y Desarrollo, Issue 19, pp. 88100, 2006. ##[11] A. R. Neshasteriz, A, KhakiSedigh and H, Sadjadian, "An Analysis of Variance Approach to Tuning of Generalized Predictive Controllers for Second Order plus Dead Time Models," 8th IEEE International Conference on Control & Automation, 2009. ##[12] L. Garriga and M. Soroush, "Model Predictive Control Tuning Methods: A Review," Ind. Eng. Chem. Res., vol. 49, pp. 3505–3515, 2010. ##[13] R. V. Hogg and J. Ledolter, Engineering statistics, MacMillan, 1987. ##[14] H. Scheffe, The Analysis of Variance, New York: Wiley, 1959. ##[15] R. A. Fisher, Statistical methods for research workers, Oliver and Boyd, Edinburgh, 1925. ##[16] R. A. Fisher, The design of experiments, Oliver and Boyd, Edinburgh, 1935. ##[17] A. M. Mora, J. J. Merelo, P. A. Castillo, J. L. J. Laredo and C. Cotta, "Influence of parameters on the performance of a MOACO algorithm for solving the bicriteria military pathfinding problem," Proceedings of the IEEE Congress on Evolutionary Computation, pp. 35073514, 2008. ##[18] V. A. Niskanen, "Prospects for integrating analysis of variance with soft computing," Information Sciences, vol. 134, pp. 135166, 2001. ##[19] K. Barbe, W. Van Moer and Y. Rolain, "Using ANOVA in a Microwave RoundRobin Comparison," IEEE Transaction on Instrument, vol. 58, pp. 34903498, Oct 2009. ##[20] J. A. D. Rodrigues, E. C. V. Toledo and R. M. Filho, "A tuned approach of the predictiveadaptive GPC controller applied to a fedbatch bioreactor using complete factorial design," Computers and Chemical Engineering, vol. 26, pp. 14931500, 2002. ##[21] R. S. Bogartz, An introduction to the analysis of variance, Praeger, Connecticut, 1994. ##[22] M. Henson and D. Seborg, "Adaptive nonlinear control of a pH neutralization process," IEEE Trans. Control Syst. Technol., vol. 2, pp. 169–182, 1994. ##[23] J. Nie, A. P. Loh, and C. C. Hang, "Modeling pH neutralization process using fuzzyneural approaches," Journal of fuzzy sets and systems, vol. 78, pp. 522, 1996. ##[24] D. Dougherty and D. Cooper, "A practical multiple model adaptive strategy for singleloop MPC," Control Engineering Practice, vol. 11, pp. 141–159, 2003. ##]