ORIGINAL_ARTICLE
Friction Compensation for Dynamic and Static Models Using Nonlinear Adaptive Optimal Technique
Friction is a nonlinear phenomenon which has destructive effects on performance of control systems. To obviate these effects, friction compensation is an effectual solution. In this paper, an adaptive technique is proposed in order to eliminate limit cycles as one of the undesired behaviors due to presence of friction in control systems which happen frequently. The proposed approach works for nonlinear dynamic and static friction models and is applicable to a wide range of different mechanical systems. It is also applied to a simple inverted pendulum on a cart as a highly nonlinear under-actuated system. A nonlinear optimal controller based on the approximate solution of Hamilton-Jacobi-Bellman partial differential equation is designed to fulfill our control objectives and achieve preferable performance compared to those of the linear optimal controllers. It causes to have more accuracy in system's response and positioning in the presence of friction. Simulation result approve the effectiveness of both the presented technique and controller.
https://miscj.aut.ac.ir/article_530_5b02f9549f0042bbf86411a581f6a900.pdf
2014-05-22T11:23:20
2018-11-16T11:23:20
1
10
10.22060/miscj.2014.530
Adaptive technique
friction compensation
HJB partial differential equation
inverted pendulum on a cart
nonlinear optimal controller
M.
Nazari Monfared
true
1
M.Sc. student of Control Engineering in the Department of Electrical Engineering, Faculty of Electrical, Biomedical, and Mechatronic, Qazvin Branch, Islamic Azad University, Qazvin, Iran
M.Sc. student of Control Engineering in the Department of Electrical Engineering, Faculty of Electrical, Biomedical, and Mechatronic, Qazvin Branch, Islamic Azad University, Qazvin, Iran
M.Sc. student of Control Engineering in the Department of Electrical Engineering, Faculty of Electrical, Biomedical, and Mechatronic, Qazvin Branch, Islamic Azad University, Qazvin, Iran
AUTHOR
M. J.
Yazdanpanah
true
2
Professor, Control & Intelligent Processing Center of Excellence, School of Electrical and Computer Engineering, University of Tehran, Tehran, Iran
Professor, Control & Intelligent Processing Center of Excellence, School of Electrical and Computer Engineering, University of Tehran, Tehran, Iran
Professor, Control & Intelligent Processing Center of Excellence, School of Electrical and Computer Engineering, University of Tehran, Tehran, Iran
LEAD_AUTHOR
[1] Morteza Nazari Monfared and Mohammad Javad Yazdanpanah, “Adaptive Compensation Technique for Nonlinear Dynamic and Static Models of Friction,” Electrical Engineering (ICEE), 23nd Iranian Conference on IEEE.
1
[2] Armstrong-Hélouvry, Brian, Pierre Dupont, and Carlos Canudas De Wit,“A survey of models, analysis tools and compensation methods for the control of machines with friction,” Automatica, vol. 30, no. 7, pp.1083-1138, 1994.
2
[3] De Wit, C. Canudas, and et al, “A new model for control of systems with friction”. Automatic
3
Control, IEEE Transactions on, vol. 40, no. 3, pp. 419-425, 1995.
4
[4] Olsson, Henrik. Control systems with friction. Diss. Lund University, 1996.
5
[5] Dupont, Pierre, and et al.,“Single state elastoplastic friction models,” Automatic Control, IEEE Transactions on, vol. 47, no. 5, pp. 787-792, 2002.
6
[6] Al-Bender, Farid, Vincent Lampaert, and Jan Swevers, “The generalized Maxwell-slip model: a novel model for friction simulation and compensation,” Automatic Control, IEEE Transactions on, vol. 50, no. 11, pp. 1883-1887, 2005.
7
[7] Kermani, Mehrdad R., Rajnikant V. Patel, and Mehrdad Moallem, “Friction identification and compensation in robotic manipulators,” Instrumentation and Measurement, IEEE Transactions on, vol. 56, no. 6, pp. 2346-2353, 2007.
8
[8] Hensen, Ron HA, Marinus JG van de Molengraft, and Maarten Steinbuch, “Frequency domain identification of dynamic friction model parameters,” Control Systems Technology, IEEE Transactions on, vol. 10, no. 2, pp.191-196, 2002.
9
[9] Wang, Yongfu, Dianhui Wang, and Tianyou Chai, “Extraction and adaptation of fuzzy rules for friction modeling and control compensation,” Fuzzy Systems, IEEE Transactions on, vol. 19, no. 4, pp. 682-693, 2011.
10
[10] Makkar, Charu, and et al., “Lyapunov-based tracking control in the presence of uncertain nonlinear parameterizable friction”. Automatic Control, IEEE Transactions on, vol. 52, no. 10, pp. 1988-1994, 2007.
11
[11] De Wit, C. Canudas, and Pablo Lischinsky, “Adaptive friction compensation with partially known dynamic friction model,”International journal of adaptive control and signal processing vol. 11, pp. 65-80, 1998.
12
[12] Kelly, Rafael, Jesús Llamas, and Ricardo Campa., “A measurement procedure for viscous and coulomb friction,” Instrumentation and Measurement, IEEE Transactions on, vol. 49, no. 4, pp. 857-861, 2000.
13
[13] Rizos D., and S. Fassois, “Friction identification based upon the LuGre and Maxwell slip models,” Control Systems Technology, IEEE Transactions on, vol. 17, no.1, pp. 153-160, 2009.
14
[14] Campbell, Sue Ann, Stephanie Crawford, and Kirsten Morris, “Friction and the inverted pendulum stabilization problem,” Journal of Dynamic Systems, Measurement, and Control, vol. 130, no. 5, pp. 054502, 2008.
15
[15] Kirk, Donald E. Optimal control theory: an introduction. Courier Corporation, 2012.
16
[16] Navasca, C. L., and A. J. Krener,“Solution of hamilton jacobi bellman equations,” Decision and Control, 2000. Proceedings of the 39th IEEE Conference on., vol. 1, 2000.
17
[17] Hunt, Thomas, and Arthur J. Krener,”Improved patchy solution to the Hamilton-Jacobi-Bellman equations,” CDC, 2010.
18
[18] Beard, Randal W., George N. Saridis, and John T. Wen,”Galerkin approximations of the generalized Hamilton-Jacobi-Bellman equation,” Automatica, vol. 33, no. 12, pp. 2159-2177, 1997.
19
[19] Sassano, Mario, and Alessandro Astolfi, “Dynamic solution of the HJB equation and the optimal control of nonlinear systems,” Decision and Control (CDC), 49th IEEE Conference on, 2010.
20
[20] Milasi, Rasoul M., Mohammad‐Javad Yazdanpanah, and Caro Lucas,“Nonlinear optimal control of washing machine based on approximate solution of HJB equation,” Optimal Control Applications and Methods, vol. 29, no. 1, pp. 1-18, 2008.
21
[21] P. Ioannou and Bariş Fidan. Adaptive Control Tutorial. Society for Industrial and applied mathematics, Philadelphia, USA, 2006.
22
[22] Ioannou, Petros A., Elias B. Kosmatopoulos, and Alvin M. Despain, “Position error signal estimation at high sampling rates using data and servo sector measurements,” Control Systems Technology, IEEE Transactions on, vol. 11, no. 3, pp. 325-334, 2003.
23
ORIGINAL_ARTICLE
Pole Assignment Of Linear Discrete-Time Periodic Systems In Specified Discs Through State Feedback
The problem of pole assignment, also known as an eigenvalue assignment, in linear discrete-time periodic systems in discs was solved by a novel method which employs elementary similarity operations. The former methods tried to assign the points inside the unit circle while preserving the stability of the discrete time periodic system. Nevertheless, now we can obtain the location of eigenvalues in the specified discs, randomly. An illustrative example with random system matrices is presented in order to show the effectiveness of the method.
https://miscj.aut.ac.ir/article_531_63ed4882a051ee437aee94f61dafb89f.pdf
2014-05-22T11:23:20
2018-11-16T11:23:20
11
17
10.22060/miscj.2014.531
Pole assignment
periodic systems
discrete-time systems
state feedback matrix
eigenvalues
closed-loop matrix
control theory
H. A.
Tehrani
true
1
Assistant Professor, Department of Mathematics, Shahrood University, Shahrood, Iran
Assistant Professor, Department of Mathematics, Shahrood University, Shahrood, Iran
Assistant Professor, Department of Mathematics, Shahrood University, Shahrood, Iran
LEAD_AUTHOR
[1] F.A. Aliev, C.C. Arcasoy, V.B. Larin, and N.A.Safarova, “Synthesis problem for periodic systems
1
by static output feedback,” Applied and Computational Mathematics. vol 4(2),pp. 102–113, 2005.
2
[2] F.A. Aliev, C.C. Arcasoy, V.B. Larin, and N.A.Safarova, “Synthesis problem for periodic systems
3
by static output feedback,” Applied and Computational Mathematics. vol 4(2),pp. 102–113, 2005.
4
[3] P. Benner, M. Castillo, and E.S Quintana-orti,“Partial stabilization of large-scale discrete-time
5
linear control systems,” Technical Report,University of Bremen, Germany. March 2001.
6
[4] J. H. Chou, “Pole assignment robustness in a specified disk,” Systems & Control Letters, vol 16, pp. 41-44, 1991.
7
[5] C. Farges, D. Peaucelle, and D. Arzelier,” Resilient static output feedback stabilization of linear periodic systems,” In: 5th IFAC Symposium on Robust Control Design, Toulouse 2006.
8
[6] C. Farges, D. Peaucelle, D. Arzelier, and J. Daafouz, “Robust performance analysis and synthesis of linear polytopic discrete-time periodic systems via LMIs,” Systems & Control Letters, vol 56(2), pp. 159.166, 2007.
9
[7] M. M. Fateh, H. Ahsani Tehrani, and S. M. Karbassi, “Repetitive control of electrically driven robot manipulators,” International Journal of Systems Science, Published Online: 18 Oct 2011.
10
[8] J. L. Figueroa and J. A. Romagnoli, “An algorithm for robust pole assignment via polynomial approach,” IEEE Transactions on Automatic Control, vol 39,pp. 831-835,1994.
11
[9] K. Furuta and S. B. Kim, “Pole assignment in a specified disk,” IEEE Transactions on Automatic Control, vol 32, pp. 423-427, 1987.
12
[10] L. Grammont and A. Largillier, “Krylov method revisited with an application to the localization of eigenvalues ,” Numerical Functional Analysis and Optimization, vol 27, pp. 583-618,
13
[11] G. Guo, J.F. Qiao, and C.Z. Han, “Controllability of periodic systems: continuous and discrete,” in proc IEE Control Theory and Applications, vol 151, pp. 488-490, 2004.
14
[12] S.M. Karbassi and D.J. Bell, “Parametric time-optimal control of linear discrete-time systems by state feedback-Part 1: Regular Kronecker invariants,” International Journal of Control, vol. 57, pp. 817-830, 1993.
15
[13] S.M. Karbassi and D.J. Bell, “Parametric time-optimal control of linear discrete-time systems by state feedback-Part 2: Irregular Kronecker invariants,” International Journal of Control, vol 57, pp. 831-839,1993.
16
[14] S.M. Karbassi and H.A. Tehrani, “Parameterizations of the state feedback controllers for linear multivariable systems ,” Computers and Mathematics with Applications, vol 44, pp. 1057-1065, 2002.
17
[15] B.P. Lampe and E. N. Rossenwasser, “Closed formulae for the L2-norm of linear continuous-time periodic systems ,” In: Proc. PSYCO, 231-236, Japan 2004.
18
[16] B.P. Lampe, M. A. Obraztso, and E. N. Rosenwasser, “Statistical analysis of stable
19
FDLCP systems by parametric transfer matrices ,” International Journal of Control, vol 78(10), pp. 747-761, 2005.
20
[17] S. Longhi, and R. Zulli, “A note on robust pole assignment for periodic systems,” IEEE Transactions on Automatic Control, vol 41, pp. 1493-1497, 1996.
21
[18] C.E.De. Souza and A. Trono, “An LMI approach to stabilization of linear discrete-time periodic systems,” International Journal of Control, vol 73, pp. 696-703, 2000.
22
[19] A. Varga, “Computation of l-infinity norm of linear discrete-time periodic systems,” In: Proc. MTNS 2006.
23
[20] J. Zhou and T. Hagiwara, “H2 and H-infinity norm computations of linear continuous-time periodic systems via the skew analysis of frequency response operators,” Automatica, vol 38, pp. 1381-1387, 2002.
24
ORIGINAL_ARTICLE
A Clustering Approach to Scientific Workflow Scheduling on the Cloud with Deadline and Cost Constraints
One of the main features of High Throughput Computing systems is the availability of high power processing resources. Cloud Computing systems can offer these features through concepts like Pay-Per-Use and Quality of Service (QoS) over the Internet. Many applications in Cloud computing are represented by workflows. Quality of Service is one of the most important challenges in the context of scheduling scientific workflows. On the other hand, the remarkable growth of the multicore processor technology has led to the use of these processors by service providers as building blocks of their infrastructure. Therefore, scheduling scientific workflows on the Cloud requires especial attention to multicore processor infrastructure which adds more challenges to the problem. On the other hand, in addition to these challenges users’ QoS constraints like execution time and cost should be regarded. The main objective of this research is scheduling workflows on the Cloud, considering a multicore based infrastructure. A new algorithm is proposed which finds clusters of the workflow that can be executed in parallel while having large data communications. These kinds of clusters could be appropriate candidates to be executed on a multicore processor. In contrast, there are other clusters which should be executed in serial. This algorithm investigates whether serial execution of these clusters is possible or not. The experimental results show that the algorithm has a positive effect on execution time and cost of the workflow execution.
https://miscj.aut.ac.ir/article_532_1c07c22360b9bfb0b797f372b5ec5471.pdf
2014-05-22T11:23:20
2018-11-16T11:23:20
19
29
10.22060/miscj.2014.532
High Throughput Computing
Cloud computing
Workflow scheduling
clustering
Time Overlap
Arash
Deldari
arash.deldari@stu-mail.um.ac.ir
true
1
Department of Computer Engineering, Ferdowsi University of Mashhad, Mashhad, IRAN
Department of Computer Engineering, Ferdowsi University of Mashhad, Mashhad, IRAN
Department of Computer Engineering, Ferdowsi University of Mashhad, Mashhad, IRAN
AUTHOR
Mahmoud
Naghibzadeh
naghibzadeh@um.ac.ir
true
2
Department of Computer Engineering, Ferdowsi University of Mashhad, Mashhad, IRAN
Department of Computer Engineering, Ferdowsi University of Mashhad, Mashhad, IRAN
Department of Computer Engineering, Ferdowsi University of Mashhad, Mashhad, IRAN
LEAD_AUTHOR
Saeid
Abrishami
s-abrishami@um.ac.ir
true
3
Department of Computer Engineering, Ferdowsi University of Mashhad, Mashhad, IRAN
Department of Computer Engineering, Ferdowsi University of Mashhad, Mashhad, IRAN
Department of Computer Engineering, Ferdowsi University of Mashhad, Mashhad, IRAN
AUTHOR
Amin
Rezaeian
amin.rezaeian@stu-mail.um.ac.ir
true
4
Department of Computer Engineering, Ferdowsi University of Mashhad, Mashhad, IRAN
Department of Computer Engineering, Ferdowsi University of Mashhad, Mashhad, IRAN
Department of Computer Engineering, Ferdowsi University of Mashhad, Mashhad, IRAN
AUTHOR
[1] S. Abrishami, M. Naghibzadeh, and D. H. J. Epema, “Cost-driven scheduling of grid workflows using partial critical paths,” Parallel IEEE Trans. on Distrib. Syst., vol. 23, no. 8, pp. 1400–1414, 2012.
1
[2] L. F. Bittencourt and E. R. M. Madeira, “HCOC: a cost optimization algorithm for workflow scheduling in hybrid clouds,” J. Internet Serv. Appl., vol. 2, no. 3, pp. 207–227, 2011.
2
[3] R. G. Michael and S. J. David, “Computers and intractability: a guide to the theory of NP-completeness,” WH Free. Co., San Fr., 1979.
3
[4] A. Abraham, R. Buyya, B. Nath, and others, “Nature’s heuristics for scheduling jobs on computational grids,” in The 8th IEEE international conference on advanced computing and communications (ADCOM 2000), pp. 45–52, 2000.
4
[5] A. K. Aggarwal and R. D. Kent, “An adaptive generalized scheduler for grid applications,” in 19th International Symposium on High Performance Computing Systems and Applications, HPCS 2005., pp. 188–194, 2005.
5
[6] M. Aggarwal, R. D. Kent, and A. Ngom, “Genetic algorithm based scheduler for computationalgrids,” in 19th International Symposium on High Performance Computing Systems and Applications, HPCS 2005., , pp. 209–215, 2005.
6
[7] A. H. Alhusaini, V. K. Prasanna, and C. S. Raghavendra, “A unified resource scheduling framework for heterogeneous computing environments,” in Proceedings. Eighth Heterogeneous Computing Workshop, 1999.(HCW’99), pp. 156–165, 1999.
7
[8] R. Bajaj and D. P. Agrawal, “Improving scheduling of tasks in a heterogeneous environment,” IEEE Trans.Parallel Distrib. Syst., vol. 15, no. 2, pp. 107–118, 2004.
8
[9] S. K. Garg, C. S. Yeo, A. Anandasivam, and R. Buyya, “Environment-conscious scheduling of HPC applications on distributed cloud-oriented data centers,” J. Parallel Distrib. Comput., vol. 71, no. 6, pp. 732–749, 2011.
9
[10] A. Beloglazov, J. Abawajy, and R. Buyya, “Energy-aware resource allocation heuristics for efficient management of data centers for cloud computing,” Futur. Gener. Comput. Syst., vol. 28, no. 5, pp. 755–768, 2012.
10
[11] A. J. Younge, G. Von Laszewski, L. Wang, S. Lopez-Alarcon, and W. Carithers, “Efficient resource management for cloud computing environments,” in International Green Computing Conference , pp. 357–364, 2010.
11
[12] A. Nathani, S. Chaudhary, and G. Somani, “Policy based resource allocation in IaaS cloud,” Futur. Gener. Comput. Syst., vol. 28, no. 1, pp. 94–103, 2012.
12
[13] W. Wang, G. Zeng, D. Tang, and J. Yao, “Cloud-DLS: Dynamic trusted scheduling for Cloud computing,” Expert Syst. Appl., vol. 39, no. 3, pp. 2321–2329, 2012.
13
[14] M. E. Frîncu, “Scheduling highly available applications on cloud environments,” Futur. Gener. Comput. Syst., vol. 32, pp. 138–153, 2014.
14
[15] M. Maheswaran, S. Ali, H. J. Siegel, D. Hensgen, and R. F. Freund, “Dynamic mapping of a class of independent tasks onto heterogeneous computing systems,” J. Parallel Distrib. Comput., vol. 59, no. 2, pp. 107–131, 1999.
15
[16] K. Etminani and M. Naghibzadeh, “A min-min max-min selective algorihtm for grid task scheduling,” in 3rd IEEE/IFIP International Conference in Central Asia on Internet, ICI 2007., pp. 1–7, 2007.
16
[17] H. Topcuoglu, S. Hariri, and M. Wu, “Performance-effective and low-complexity task scheduling for heterogeneous computing,” IEEE
17
Trans. Parallel Distrib. Syst., vol. 13, no. 3, pp. 260–274, 2002.
18
[18] T. Yang and A. Gerasoulis, “A fast static scheduling algorithm for DAGs on an unbounded number of processors,” in Proceedings of the 1991 ACM/IEEE conference on Supercomputing, pp. 633–642, 1991.
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[19] V. Sarkar, Partitioning and scheduling parallel programs for multiprocessors. MIT press, 1989.
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[20] L. F. Bittencourt and E. R. M. Madeira, “A performance-oriented adaptive scheduler for dependent tasks on grids,” Concurr. Comput. Pract. Exp., vol. 20, no. 9, pp. 1029–1049, 2008.
21
[21] L. F. Bittencourt and E. R. M. Madeira, “Towards the scheduling of multiple workflows on computational grids,” J. grid Comput., vol. 8, no. 3, pp. 419–441, 2010.
22
[22] S. Abrishami, M. Naghibzadeh, and D. H. J. Epema, “Deadline-constrained workflow scheduling algorithms for Infrastructure as a Service Clouds,” Futur. Gener. Comput. Syst., vol. 29, no. 1, pp. 158–169, 2013.
23
[23] D. Poola, S. K. Garg, R. Buyya, Y. Yang, and K. Ramamohanarao, “Robust scheduling of scientific workflows with deadline and budget constraints in clouds,” in The 28th IEEE International Conference on Advanced Information Networking and Applications (AINA-2014), pp. 1–8, 2014.
24
[24] H. Kanemitsu, M. Hanada, T. Hoshiai, and H. Nakazato, “Effective use of computational resources in multi-core distributed systems,” in 16th International Conference on Advanced Communication Technology (ICACT), 2014, pp. 305–314, 2014.
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[25] E. Deelman, G. Singh, M.-H. Su, J. Blythe, Y. Gil, C. Kesselman, G. Mehta, K. Vahi, G. B. Berriman, J. Good, and others, “Pegasus: A framework for mapping complex scientific workflows onto distributed systems,” Sci. Program., vol. 13, no. 3, pp. 219–237, 2005.
26
[26] S. Bharathi, A. Chervenak, E. Deelman, G. Mehta, M.-H. Su, and K. Vahi, “Characterization of scientific workflows,” in Third Workshop on Workflows in Support of Large-Scale Science, 2008. WORKS 2008., pp. 1–10, 2008.
27
ORIGINAL_ARTICLE
An ECC-Based Mutual Authentication Scheme with One Time Signature (OTS) in Advanced Metering Infrastructure
Advanced metering infrastructure (AMI) is a key part of the smart grid; thus, one of the most important concerns is to offer a secure mutual authentication. This study focuses on communication between a smart meter and a server on the utility side. Hence, a mutual authentication mechanism in AMI is presented based on the elliptic curve cryptography (ECC) and one time signature (OTS) consists of two phases: a key and signature generation phase as well as a signature verification phase. The next challenge, is securing communication messages. Accordingly, a message authentication mechanism based on ECC and OTS is proposed in this paper. Such protocols are designed based on resource constraint problem on the consumer side and security requirement satisfaction in AMI. Security of the protocol with BAN logic is proved and possibility of signature forgery via the mathematical principle of birthday paradox formula is represented. In the end, security of the protocol is scrutinized with informal methods and is simulated on Java. Simulation and analytical results show that proposed protocols are more secure and efficient than similar methods against most of the security attacks.
https://miscj.aut.ac.ir/article_533_edd8093a9dd6ed1efbb0e721465f8d9d.pdf
2014-05-22T11:23:20
2018-11-16T11:23:20
31
44
10.22060/miscj.2014.533
Advanced Metering Infrastructure
Elliptic curve
Mutual authentication
One time signature
Smart grid
Key management
F.
Naji Mohades
true
1
M.Sc. Student, Department of Computer Engineering, Imam Reza International University, Mashhad, Iran
M.Sc. Student, Department of Computer Engineering, Imam Reza International University, Mashhad, Iran
M.Sc. Student, Department of Computer Engineering, Imam Reza International University, Mashhad, Iran
AUTHOR
M. H.
Yaghmaee Moghadam
true
2
Professor, Department of Computer Engineering and Center of Excellence on Soft Computing and Intelligent Information Processing, Ferdowsi University of Mashhad, Mashhad, Iran
Professor, Department of Computer Engineering and Center of Excellence on Soft Computing and Intelligent Information Processing, Ferdowsi University of Mashhad, Mashhad, Iran
Professor, Department of Computer Engineering and Center of Excellence on Soft Computing and Intelligent Information Processing, Ferdowsi University of Mashhad, Mashhad, Iran
LEAD_AUTHOR
[1] Kim, Y.S., Heo, J., “Device Authentication Protocol for Smart Grid Systems Using Homomorphic Hash,” IEEE Network and Communication. Vol.14, pp. 606-613, 2012.
1
[2] Ray, P. D., Harnoor, R., Hentea, M., “Smart Power Grid Security: A Unified Risk Management Approach,” IEEE Int’l. Carnahan Conf. Security Tech., pp. 5–8, 2010.
2
[3] Li, X., Liang, X., Lu, R., Shen, X., Lin, X., Zhu, H., “Securing smart grid: cyber attacks, countermeasures, and challenges,” IEEE Communications Magazine, vol. 50, no. 8, pp. 38–45, 2012.
3
[4] U. S. Department of Energy, [online] Available: www.oe.energy.gov.
4
[5] Yan, Y., Hu, R.Q., Das, S.K., Sharif, H. Qian, Y., “An Efficient Security Protocol for Advanced Metering Infrastructure in Smart Grid,” IEEE Trans. Network. vol. 27, pp. 64-71, 2013.
5
[6] Wan, z., Wang, G., Yang, Y. and Shi, S., "SKM: Scalable Key Management for advanced metering infrastructure in smart grids," IEEE Trans. Ind. Electron., vol. 61, no. 12, pp.7055 -7066, 2014.
6
[7] Li, H., Lu, R., Zhou, L., Yang, B., Shen, x., "An Efficient Merkle-Tree-Based Authentication Scheme for Smart Grid," Journal of System IEEE trans., pp. 655 - 663, 2014.
7
[8] Saputro, N. and Akkaya, K., “On preserving user privacy in smart grid advanced metering infrastructure applications,” Security Commun. Netw., vol. 7, no. 1, pp. 206–220, 2014.
8
[9] Li, Q., Cao, G, “Multicast Authentication in Smart Grid with One-Time Signature. IEEE Trans. smart grid,” pp. 686-696, 2011.
9
[10] Metke, A. R., Ekl, R. L., “Security technology for smart grid networks,” IEEE Trans. Smart Grid, vol. 1, iss. 1, pp. 99–107, 2010.
10
[11] Miller, V.S., “Use of Elliptic Curves in Cryptography,” Advances in Cryptology — CRYPTO ’85 Proceedings, pp. 417-426, 1986.
11
[12] Koblitz, N., “Elliptic curve cryptosystems,” Mathematics of Computation, pp. 203–209. JSTOR 2007884, 1987.
12
[13] Lamport, L., “Constructing digital signatures from a one way function,” Technical Report. CSL-98, SRI International, 1979.
13
[14] Rabin, M.O., “Digitalized signatures,” In Richard A. Demillo, David P. Dobkin, Anita K. Jones, and Richard J. Lipton, editors, Foundations of Secure Computation, 1978.
14
[15] Merkle, R.C., “Secrecy, authentication, and public key systems,” UMI Research Press, 1982.
15
[16] Gao, W., Li, Q., Zhao, B., Cao, G., “Multicasting in delay tolerant networks: a social network perspective,” ACM, New York, pp. 299-308, 2009.
16
[17] Reyzin, L., Reyzin, N., “Better than BiBa: Short one-time signatures with fast signing and verifying,” Proc. of the Australian Conference on Information Security and Privacy, pp. 144-153, 2002.
17
[18] Bos, J.N.E., and Chaum, D., “Provably unforgeable signatures,” Advances in Cryptography-CRYPTO, pp.1-14, 1993.
18
[19] Menezes, A.J., Oorschot, P.C.V., Vanstone, S.A. “Handbook of Applied Cryptography,” CRC Press LLC, USA, pp. 52-53, 1997.
19
[20] Yaghmaee, M.H., Naji.M, F, “A Lightweight Mechanism for Mutual Authentication in Smart Grid,” Challenges of Implementing Active Distribution System Managment.0223. Cired Workshop 2014.
20
[21] Perring, A, “The BiBa one-time signature and broadcast authentication protocol,” Proceedings of the 8th ACM conference on Computer and Communication security, pp. 28-37, 2001.
21
[22] Kgwadi, M., Kunz, T., “Securing RDS broadcast messages for smart grid applications,” In Proceeding of the 6th International Wireless Communications and Mobile Computing, ACM Conference, pp. 1177-1181, 2010.
22
[23] Burrow, M., Abad, M., Needham, R., “A logic of authentication,” ACM Trans. Comput. Syst. 8, pp. 18–36, 1990.
23
[24] Syverson, P., Cervesato, I., “The logic of authentication protocols,” in: Foundations of Security Analysis and Design, Tutorial Lectures, in: Lecture Notes in Comput. Sci., vol. 2171, Springer, pp. 63–136, 2001.
24
[25] Certicom Research, SEC2: Recommended elliptic curve domain parameters v1.0, 2000.
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[26] Shamus Software Ltd., Miracl Library, <http://www.shamus.ie/index.php?page=home>.
26
[27] Debiao, H., Jianhua, Ch., and Jin, H., “An ID-based client authentication with key agreement protocol for mobile client–server environment on ECC with provable security,” elsevier, journal of Information Fusion, pp. 223-230, 2012.
27
ORIGINAL_ARTICLE
On The Simulation of Partial Differential Equations Using the Hybrid of Fourier Transform and Homotopy Perturbation Method
In the present work, a hybrid of Fourier transform and homotopy perturbation method is developed for solving the non-homogeneous partial differential equations with variable coefficients. The Fourier transform is employed with combination of homotopy perturbation method (HPM), the so called Fourier transform homotopy perturbation method (FTHPM) to solve the partial differential equations. The closed form solutions obtained from the series solution of recursive sequence forms are obtained. We show that the solutions to the non-homogeneous partial differential equations are valid for the entire range of problem domain. However the validity of the solutions using the previous semi-analytical methods in the entire range of problem domain fails to exist. This is the deficiency of the previous HPMs caused by unsatisfied boundary conditions that is overcome by the new method, the Fourier transform homotopy perturbation method. Moreover, it is shown that solutions approach very rapidly to the exact solutions of the partial differential equations. The effectiveness of the new method for three non-homogenous differential equations with variable coefficients is shown schematically. The very rapid approach to the exact solutions is also shown schematically.
https://miscj.aut.ac.ir/article_534_6f2582acab31e05339715b4ef4f00c5c.pdf
2014-05-22T11:23:20
2018-11-16T11:23:20
45
55
10.22060/miscj.2014.534
Fourier transformation
Homotopy Perturbation Method
Non-homogeneous partial differential equation
S. S.
Nourazar
true
1
Associate Professor, Department of Mechanical Engineering, Amirkabir University of Technology, Tehran, Iran
Associate Professor, Department of Mechanical Engineering, Amirkabir University of Technology, Tehran, Iran
Associate Professor, Department of Mechanical Engineering, Amirkabir University of Technology, Tehran, Iran
AUTHOR
A.
Mohammadzadeh
true
2
Researcher, Tehran university alumnus in mechanical engineering, Tehran, Iran
Researcher, Tehran university alumnus in mechanical engineering, Tehran, Iran
Researcher, Tehran university alumnus in mechanical engineering, Tehran, Iran
AUTHOR
M.
Nourazar
true
3
M.Sc. Student, Department of Physics, Helsinki University, Helsinki, Finland
M.Sc. Student, Department of Physics, Helsinki University, Helsinki, Finland
M.Sc. Student, Department of Physics, Helsinki University, Helsinki, Finland
LEAD_AUTHOR
[1] J. H. He, “Non-perturbative Methods for Strongly Nonlinear Problems,” dissertation.de-Verlag im Internet GmbH, Berlin, 2006.
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[2] J. H. He, “Some asymptotic methods for strongly nonlinear equations,” Int. J. Mod. Phys., vol. B 20, no. 10, pp. 1141-1199, 2006.
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[3] J. H. He, “Homotopy perturbation method for solving boundary value problems,” Phys. Lett., vol. A 350, no. 1–2, pp. 87-88, 2006.
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[4] J. H. He, “Application of homotopy perturbation method to nonlinear wave equations,” Chaos Solitons Fractals, vol. 26, no. 3, pp. 695-700, 2005.
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[5] J. H. He, “Approximate analytical solution for seepage flow with fractional derivatives in porous media,” Comput. Math. Appl. Mech. Eng., vol. 167, pp. 57-68, 1998.
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[6] J. H. He, “Approximate solution of nonlinear differential equations with convolution product nonlinearities,” Comput. Math. Appl. Mech. Eng., vol. 167, pp. 69-73, 1998.
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[7] J. H. He, “Variational iteration method – a kind of non-linear analytical technique: some examples,” Int. J. Non-Linear Mech., vol. 34, pp. 699-708, 1999.
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[8] J. H. He, “Homotopy perturbation technique,” J. Comput. Math. Appl. Mech. Eng., vol. 178, pp. 257-262, 1999.
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[9] J. H. He, “A coupling method of a homotopy technique and a perturbation technique for non-
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linear problems,” Int. J. Non-Linear Mech., vol. 35, pp. 37-43, 2000.
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[10] J. H. He, X.H. Wu, “Construction of solitary solution and compacton-like solution by variational iteration method,” Chaos Solitons Fractals, vol. 29, no. 1, pp. 108-113, 2006.
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[11] J. H. He, “Periodic solutions and bifurcations of delay-differential equations,” Phys. Lett., vol. A 347, no. 4–6, pp. 228-230, 2005.
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[12] J. H. He, “Limit cycle and bifurcation of nonlinear problems, Chaos Solitons Fractals,” vol. 26, no. 3, pp. 827-833, 2005.
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[13] J. H. He, “Homotopy perturbation method for bifurcation of nonlinear problemsint,” J. Nonlinear Sci. Numer. Simul., vol. 6, no. 2, pp. 207-208, 2005.
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[14] B. Jang, “Two-point boundary value problems by extended Adomian decomposition method,” J. of Comput. and Appl. Math. vol. 219, pp. 253–262, 2008.
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[15] M. Madani, M. Fathizadeh, Y. Khan and A. Yildirim, “On the coupling of the homotopy perturbation method and Laplace transformation,” J. Mathematical and Computer Modelling, vol. 53 no. 9-10, pp. 1937-1945, 2011.
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plate, Chaos Solitons Fractals,” I. S. J. of Thermal Scince, vol. 42, no. 4, pp. 2413-2419, 2009.
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[21] partial and non linear differential equations, World J. Modelling Simul., vol. 5, no. 3, pp. 225-231, 2009.
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[34] S. Nourazar, A. Nazari-Golshan, A. Yildrim and M. Nourazar, “On the hybrid of Fourier transform and Adomian decomposition method for the solution of nonlinear Cauchy problems of the reaction-diffusion equation,” Z. Naturforsch, vol. 67a, pp. 355-362, 2012.
37
ORIGINAL_ARTICLE
(n,1,1,α)-Center Problem
Given a set of points in the plane and a constant ,-center problem is to find two closed disks which each covers the whole , the diameter of the bigger one is minimized, and the distance of the two centers is at least . Constrained -center problem is the -center problem in which the centers are forced to lie on a given line . In this paper, we first introduce -center problem and its constrained version. Then, we present an algorithm for solving the -center problem. Finally, we propose a linear time algorithm for its constrained version.
https://miscj.aut.ac.ir/article_535_e55e97bdb7319ea3d4097b5b4d3a2123.pdf
2014-05-22T11:23:20
2018-11-16T11:23:20
57
64
10.22060/miscj.2014.535
computational geometry
K-Center Problem
Farthest Point Voronoi Diagram
Center Hull
P.
Kavand
true
1
PhD. Student of Computer Science, Department of Mathematics and Computer Science, Amirkabir University of Technology, Tehran, Iran.
PhD. Student of Computer Science, Department of Mathematics and Computer Science, Amirkabir University of Technology, Tehran, Iran.
PhD. Student of Computer Science, Department of Mathematics and Computer Science, Amirkabir University of Technology, Tehran, Iran.
AUTHOR
A.
Mohades
true
2
Associate Professor, Department of Mathematics and Computer Science, Amirkabir University of Technology, Tehran, Iran
Associate Professor, Department of Mathematics and Computer Science, Amirkabir University of Technology, Tehran, Iran
Associate Professor, Department of Mathematics and Computer Science, Amirkabir University of Technology, Tehran, Iran
LEAD_AUTHOR
M.
Eskandari
true
3
Assistant Professor, Department of Mathematics, Alzahra University, Tehran, Iran
Assistant Professor, Department of Mathematics, Alzahra University, Tehran, Iran
Assistant Professor, Department of Mathematics, Alzahra University, Tehran, Iran
AUTHOR
[1] Rezaei, M., and FazelZarandi, M.H., “Facility location via fuzzy modeling and simulation,” Applied soft computing, Vol. 11, pp. 5330– 5340, 2011.
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[5] Megiddo, N., “Linear time algorithms for linear programming in ℝ3,” Society for Industrial and Applied Mathematics, Vol. 12, No. 4. November 1983.
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[6] Drezner, Z., “The planar two-center and two-median problems,” Transportation Science, Vol. 18, pp. 351- 361, 1984.
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[7] Hershberger, J., and Suri, S., “Finding tailored partitions,” J. Algorithms, Vol.12, pp. 431– 463, 1991.
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[8] Agarwal, P. K., and Sharir, M., “Planar geometric location problems,” Algorithmica, Vol.11, pp. 185– 195, 1994.
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[9] Megiddo, N., “Applying parallel computation algorithms in the design of serial algorithms,” J. ACM, Vol.30, pp. 852– 865, 1983.
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[10] Eppstein, D., “Dynamic three-dimensional linear programming,” ORSA J. Computing, Vol.4, pp. 360– 368, 1992.
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[12] Sharir, M., “A near linear algorithm for the planar 2-center problem,” Discrete Comput. Geom., Vol.18, pp. 125– 134, 1997.
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[13] Eppstein, D., “Faster construction of planar two-centers,” Proc. 8th ACM-SIAM Sympos. Discrete Algorithms, pp. 131– 138, 1997.
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[14] Chan, T. M., “More planar two-center algorithms,” Comput. Geom. Theory Appl., Vol.13, pp. 189– 198, 1999.
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[15] Huang, P. H., Tsai, Y. T., and Tang, C. Y., “A near-quadratic algorithm for the alpha-connected two-center problem,” Journal Of Information Science and Engineering, Vol. 22, pp. 1317- 1324, 2006.
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[16] Huang, P. H., Tsai, Y. T., and Tang, C. Y., “A fast algorithm for the alpha-connected two-center decision problem,” Information Processing Letters, Vol. 85, pp. 205- 210, 2003.
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[17] Rao, A. S., Goldberg, K., “Manipulating algebraic parts in the plane,” Technical Report RUU-CS-93-43, 1993.
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[18] Preparata, F. P., and Shamos, M. I., “Computational Geometry: An Introduction,” Springer Verlag, New York, 1985.
18