2014
46
2
2
0
Microwave Imaging Using SAR
Microwave Imaging Using SAR
2
2
Polarimetric Synthetic Aperture Radar (Pol.-SAR) allows us to implement the recognition and classification of radar targets. This article investigates the arrangement of scatterers by SAR data and proposes a new Look-up Table of Region (LTR). This look-up table is based on the combination of (entropy H/Anisotropy A) and (Anisotropy A/scattering mechanism α), which has not been reported up now. First of all, the color coded images of each of the quantities of H, A and αare extracted and then having the matrix associated with each image and evaluating its histogram, we could obtain the image parameter values corresponding to each interval related to each color code. Then in the output the combination of parameters and the sharing of their images of each frame are extracted and compared with optical images and the extracted satellite map of scattered fields. Results for unconventional targets such as random rough surfaces has indicated that mechanism of scattering irregularities and improper alignment can be used for different purposes in different parts of the frame with fixed values that can be a new method for identifying targets. To make a look up table it is essentially required to evaluate the target parameters and classification of radar images. The method of the extraction of these parameters and applying them on imaging radar systems is exclusive. To validate our work, Pol. SAR data sets are used.
1
Polarimetric Synthetic Aperture Radar (Pol.-SAR) allows us to implement the recognition and classification of radar targets. This article investigates the arrangement of scatterers by SAR data and proposes a new Look-up Table of Region (LTR). This look-up table is based on the combination of (entropy H/Anisotropy A) and (Anisotropy A/scattering mechanism α), which has not been reported up now. First of all, the color coded images of each of the quantities of H, A and αare extracted and then having the matrix associated with each image and evaluating its histogram, we could obtain the image parameter values corresponding to each interval related to each color code. Then in the output the combination of parameters and the sharing of their images of each frame are extracted and compared with optical images and the extracted satellite map of scattered fields. Results for unconventional targets such as random rough surfaces has indicated that mechanism of scattering irregularities and improper alignment can be used for different purposes in different parts of the frame with fixed values that can be a new method for identifying targets. To make a look up table it is essentially required to evaluate the target parameters and classification of radar images. The method of the extraction of these parameters and applying them on imaging radar systems is exclusive. To validate our work, Pol. SAR data sets are used.
1
7
I.
Kalantari
I.
Kalantari
MSc. Student, Department of Electrical Engineering, Amirkabir University of Technology, Tehran, Iran
MSc. Student, Department of Electrical Engineering
Iran
B.
Zakeri
B.
Zakeri
Assistant Professor, Department of Electrical Engineering, Babol Noshirvani University of Technology, Babol, Iran
Assistant Professor, Department of Electrical
Iran
Polarimetric radars
Decomposition theorem
Covariance matrix
Estimation theory
[Storvold, R., E. Malnes, and Y. Larsen, “SAR remote sensing of snow parameters in Norwegian areas-current status and future perspective,” Journal of Electromagnetic Waves and Applications,Vol. 20, No. 13, 1751–1759, 2006.##Chan, Y. K. and S. Y. Lim, “An introduction to Synthetic Aperture Radar (SAR),” Progress in Electromagnetics Research, Vol. 2, 27–60, 2008.##Storvold, R., E. Malnes, Y. Larsen, K. A. Hogda, andS. E. Hamran, “SAR remote sensing of snow parameters in Norwegian areas-current status and future perspective,” Journal of Electromagnetic Waves and Applications, Vol. 20, No. 13, 1751–1759, 2006##Nie, X., D. Y. Zhu, and Z. D. Zhu, “Application of synthetic bandwidth approach in SAR polar format algorithm using the decamp technique,” Progress in Electromagnetics Research, PIER 80, 447–460, 2008.##Wu, B.-I., M. Yeuing, and Y. Hara, “In-SAR high in version by using 3-D phase projection with multiple baselines,” Progress InElectromagnetics Research, PIER 91, 173–193, 2009.##Lim, T. S., C.-S. Lim, and V. C. Koo, “Autofocus algorithm performance evaluations using an integrated SAR product simulator and processor,” Progress In Electromagnetics Research, PIERB, Vol. 3, 315–329, 2008.##Ebrahimi-Ganjeh, M. A. and A. R. Attari, “Study of water bolus effect on SAR penetration depth and effective field size for local hyperthermia,” Progress In Electromagnetics Research, PIER, B, Vol. 4,273–283, 2008.##S. R. Cloude, E. Pottier. “An entropy based classification scheme for land applications of Polarimetric SAR. IEEE Transactions on Geoscience and Remote Sensing, vol. 35, 1997, PP.549-557.##J .S Lee, Mo. & Grunes. Unsupervised classification using Polarimetric decomposition and the complex Wishart classifier. IEEE Transactions on Geoscience and Remote Sensing vo1.37,1999,PP.2249-2258.##E. Pottier. Unsupervised classification scheme and topography derivation of POLSAR data based on the H/α/A polarimetric decomposition theorem. In Proc. 4th International workshop on RadarPolarimetry .PP.535-548, Nantes, France, July1998.##Cloude, S. R., J. Fortuny, J. M. Lopez-Sanchez, and A. J. Sieber, “Wide-band polarimetric radar inversion studies for vegetation layers,” IEEE Transactions on Geoscience and Remote Sensing, Vol. 37, No. 5, 2430–2441, 1999.##Lopez-Martinez, C., E. Pottier, and S. R. Cloude, “Statistical assessment of eigenvector-based target decomposition theorems in radar polarimetry,” IEEE Transactions on Geoscience and Remote Sensing, Vol. 43, No. 9, 2058–2074,2005.##Cloude, S. R. and E. Pottier, “A review of target decomposition theorems in radar polarimetry,” IEEE Transactions on Geoscienceand Remote Sensing, Vol. 34, No. 2, 498–518, 1996.##J. S. Lee, M. R. Grunes. Unsupervised terrain classification preserving Polarimetric scattering characteristics. IEEE Transactions on Geoscience and Remote Sensing, vo1.42, 2004, PP.722-73I.##Zhao Li-wen, Zhou Xiao-guang, Jiang Yong-mei, Kuanggangyao. “Iterative Classification of Polarimetric SAR Image Based on the Freeman Decomposition and Scattering Entropy”. IEEE Transactions On Geoscience And Remote Sensing, vol. 7, 2007, PP.473-476.##B. Zakeri, A. Ghorbani, andH. Amindavar “A new method to extract the polarimetric parameters in imaging radars,”Progress In Electromagnetics Research, PIER 87, pp 167–182, 2008.##]
Tunable Plasmonic Nanoparticles Based on Prolate Spheroids
Tunable Plasmonic Nanoparticles Based on Prolate Spheroids
2
2
Metallic nanoparticles can exhibit very large optical extinction in the visible spectrum due to localized surface plasmon resonance. Spherical plasmonic nanoparticles have been the subject of numerous studies in recent years due to the fact that the scattering response of spheres can be analytically evaluated using Mie theory. However a major disadvantage of metallic spherical nanoparticles is that their resonance wavelength is independent of the particle dimensions. In this paper, plasmonic resonance of spheroidal metallic nanoparticles is studied. Using the quasi-static approximation, the resonance condition for localized surface plasmon of spheroidal nanoparticles is derived. It is shown that unlike spherical nanoparticles in which the resonance wavelength is independent of the particle dimensions, the additional degree of freedom in spheroids allows for tuning the resonant wavelength. Additionally a formal approach to tune the surface plasmonic resonance of nano-spheroids to a wavelength of interest is presented. The results are confirmed by performing full-wave simulation for gold nanoparticles.
1
Metallic nanoparticles can exhibit very large optical extinction in the visible spectrum due to localized surface plasmon resonance. Spherical plasmonic nanoparticles have been the subject of numerous studies in recent years due to the fact that the scattering response of spheres can be analytically evaluated using Mie theory. However a major disadvantage of metallic spherical nanoparticles is that their resonance wavelength is independent of the particle dimensions. In this paper, plasmonic resonance of spheroidal metallic nanoparticles is studied. Using the quasi-static approximation, the resonance condition for localized surface plasmon of spheroidal nanoparticles is derived. It is shown that unlike spherical nanoparticles in which the resonance wavelength is independent of the particle dimensions, the additional degree of freedom in spheroids allows for tuning the resonant wavelength. Additionally a formal approach to tune the surface plasmonic resonance of nano-spheroids to a wavelength of interest is presented. The results are confirmed by performing full-wave simulation for gold nanoparticles.
9
14
F. A.
Namin
F. A.
Namin
Assistant Professor, Department of Electrical Engineering, Amirkabir University of Technology, Tehran, Iran
Assistant Professor, Department of Electrical
Iran
Localized Surface Plasmon
Plasmonics
Spheroidal Nanoparticles
Quasi-Static Approximation
[[1] M. Hu, J. Chen, Z. Y. Li, L. Au, G. V. Hartland, X. Li, M. Marquez, and Y. Xia, “Gold nanostructures: engineering their plasmonic properties for biomedical applications,” Chem. Soc. Rev., vol. 35, pp. 1084–1094, 2006.##[2] N. Flidj, G. Laurent, J. Aubard, G. Lvi, A. Hohenau, J. R. Krenn, and F. R. Aussenegg, “Grating-induced plasmon mode in gold nanoparticle arrays,” The Journal of Chemical Physics, vol. 123, no. 22, pp. –, 2005.##[3] B. Lamprecht, G. Schider, R. T. Lechner, H. Ditlbacher, J. R. Krenn, A. Leitner, and F. R. Aussenegg, “Metal nanoparticle gratings: Influence of dipolar particle interaction on the plasmon resonance,” Phys. Rev. Lett., vol. 84, pp. 4721–4724, May 2000.##[4] C. Bauer, G. Kobiela, and H. Giessen, “2D quasiperiodic plasmonic crystals,” Sci. Rep., vol. 2, pp. 1–6, 2012.##[5] A. Gopinath, S. V. Boriskina, B. M. Reinhard, and L. Del Negro, “Deterministic aperiodic arrays of metal nanoparticles for surface-enhanced Raman scattering (SERS),” Opt. Express, vol. 17, no. 5, pp. 3741–3753, 2009.##[6] F. Le, D. W. Brandl, Y. A. Urzhumov, H. Wang, J. Kundu, N. J. Halas, J. Aizpurua, and P. Nordlander, “Metallic nanoparticle arrays: A common substrate for both surface-enhanced Raman scattering and surface-enhanced infrared absorption,” ACS Nano, vol. 2, no. 4, pp. 707–718, 2008.##[7] A. Gopinath, S. V. Boriskina, N. Feng, B. M. Reinhard, and L. Del Negro, “Photonic-plasmonic scattering resonances in deterministic aperiodic structures,” Nano Letters, vol. 8, no. 8, pp. 2423–2431, 2008.##[8] S.J Oldenburg, R.D Averitt, S.L Westcott, and N.J Halas, “Nano-engineering of optical resonances,” Chemical Physics Letters, vol. 288, no. 24, pp. 243 – 247, 1998.##[9] S. Link and M. A. El-Sayed, “Spectral properties and relaxation dynamics of surface plasmon electronic oscillations in gold and silver nanodots and nanorods,” The Journal of Physical Chemistry B, vol. 103, no. 40, pp. 8410–8426, 1999. ##[10] M.F. Pantoja, M.G. Bray, D.H. Werner, P.L. Werner, and A.R. Bretones, “A computationally efficient method for simulating metal-nanowire dipole antennas at infrared and longer visible wavelengths,” Nanotechnology, IEEE Transactions on, vol. 11, no. 2, pp. 239–246, March 2012.##[11] V. A. Podolskiy, A. K. Sarychev, E. E. Narimanov, and V. M. Shalaev, “Resonant light interaction with plasmonic nanowire systems,” Journal of Optics A: Pure and Applied Optics, vol. 7, no. 2, pp. S32, 2005.##[12] B. Luk’yanchuk, N. I. Zheludev, S. A. Maier, N. J. Halas, P. Nordlander, H. Giessen, and C. T. Chong, “The Fano resonance in plasmonic nanostructures and metamaterials,” Nature materials, vol. 9, no. 9, pp. 707–715, 2010.##[13] C. F. Bohren and D. R. Huffman, Absorption and Scattering of Light by Small Particles, Wiley-VCH, Weinheim, Germany, 2004.##[14] J. D. Jackson, Classical Electrodynamics, Wiley, New York, NY, 1975.##[15] W. Cai and V. Shalaev, Optical Metamaterials, Springer, New York, 2010.##[16] E. Krugel, The Physics of Interstellar Dust, IOP Publishing Ltd, London, UK, 2003.##[17] CST Microwave Studio 2012, CST Gmbh (http://www.cst.com), 2012.##[18] M. Quinten, Optical Properties of Nanoparticle Systems: Mie and Beyond, Wiley-VCH, Weinheim, Germany, 2011.##]
Optical Chirality Enhancement in Twisted Arrays of Plasmonic Nano-rods
Optical Chirality Enhancement in Twisted Arrays of Plasmonic Nano-rods
2
2
An important property of electromagnetic fields, which arises from the interaction between fields and chiral molecules, is called optical chirality. By enhancing this field property, while maintaining constant input power, we are able to increase absorption of circularly polarized light by chiral molecules of a certain handedness. This enhancement is achieved through the use of achiral plasmonic nano-particles in conjunction with the twisted metamaterials. Optical chirality enhancement (OCE) has an important application in sensing enantiomers of chiral molecules. Here, we present a preliminary scheme to measure enantiomeric excess in mixtures of chiral molecules using OCE boosted by twisted metamaterials. This scheme does not require measurement of a frequency shift in the circular dichroism response.
1
An important property of electromagnetic fields, which arises from the interaction between fields and chiral molecules, is called optical chirality. By enhancing this field property, while maintaining constant input power, we are able to increase absorption of circularly polarized light by chiral molecules of a certain handedness. This enhancement is achieved through the use of achiral plasmonic nano-particles in conjunction with the twisted metamaterials. Optical chirality enhancement (OCE) has an important application in sensing enantiomers of chiral molecules. Here, we present a preliminary scheme to measure enantiomeric excess in mixtures of chiral molecules using OCE boosted by twisted metamaterials. This scheme does not require measurement of a frequency shift in the circular dichroism response.
15
22
A.N.
Askarpour
A.N.
Askarpour
Assistant Professor, Department of Electrical Engineering, Amirkabir University of Technology, Tehran, Iran.
Assistant Professor, Department of Electrical
Iran
Y.
Zhao
Y.
Zhao
Faculty Member, Department of Electrical and Computer Engineering, University of Texas at Austin, Austin, TX 78712 USA.
Faculty Member, Department of Electrical
Iran
A.
Alù
A.
Alù
Associate Professor, Department of Electrical and Computer Engineering, University of Texas at Austin, Austin, TX 78712 USA.
Associate Professor, Department of Electrical
Iran
Enantiomeric Excess
Optical Chirality
Plasmonics
Twisted Metamaterial
[[1] H. D. Flack, “Louis Pasteurs discovery of molecular chirality and spontaneous resolution in 1848, together with a complete review of his crystallographic and chemical work,” Acta Crystallogr. Sect. A Found. Crystallogr., vol. 65, no. 5, pp. 371–389, 2009.##[2] T. Eriksson, S. Björkman, and P. Höglund, “Clinical pharmacology of thalidomide,” Eur. J. Clin. Pharmacol., vol. 57, no. 5, pp. 365–376, Jul. 2001.##[3] S. Erb, “Single-Enantiomer Drugs Poised for Further Market Growth,” Pharm. Technol., vol. 30, pp. s14–s18, 2006.##[4] R. W. Woody and N. Berova, Circular Dichroism: Principles and Applications. Wiley-VCH, 2000.##[5] D. M. Lipkin, “Existence of a New Conservation Law in Electromagnetic Theory,” J. Math. Phys., vol. 5, no. 5, p. 696, 1964.##[6] Y. Tang and A. E. Cohen, “Optical Chirality and Its Interaction with Matter,” Phys. Rev. Lett., vol. 104, no. 16, p. 163901, Apr. 2010.##[7] Y. Tang and A. E. Cohen, “Enhanced enantioselectivity in excitation of chiral molecules by superchiral light,” Science, vol. 332, no. 6027, pp. 333–6, Apr. 2011.##[8] D. S. Bradshaw, J. M. Leeder, M. M. Coles, and D. L. Andrews, “Signatures of material and optical chirality: Origins and measures,” Chem. Phys. Lett., vol. 626, pp. 106–110, 2015.##[9] K. Ding, J. Ng, L. Zhou, and C. T. Chan, “Realization of optical pulling forces using chirality,” Phys. Rev. A - At. Mol. Opt. Phys., vol. 89, no. 6, pp. 1–7, 2014.##[10] M. H. Alizadeh and B. M. Reinhard, “Plasmonically Enhanced Chiral Optical Fields and Forces in Achiral Split Ring Resonators,” ACS Photonics, p. 150305111408006, 2015.##[11] Y. Zhao, A. Askarpour, L. Sun, J. Shi, X. Li, and A. Alu, “High-Sensitivity Chiral Molecular Sensing with Optical Metasurfaces,” in CLEO: 2014, 2014, vol. 26, no. 9, p. FM3K.6.##[12] Y. Cui, L. Kang, S. Lan, S. Rodrigues, and W. Cai, “Giant Chiral Optical Response from a Twisted-Arc Metamaterial.,” Nano Lett., Jan. 2014.##[13] A. N. Askarpour, Y. Zhao, and A. Alù, “Wave propagation in twisted metamaterials,” Phys. Rev. B, vol. 90, no. 5, p. 054305, Aug. 2014.##[14] A. N. Askarpour, Y. Zhao, and A. Alu, “Optical chirality enhancement in twisted metamaterials,” in 2014 Third Conference on Millimeter-Wave and Terahertz Technologies (MMWATT), 2014, pp. 1–4.##[15] A. H. Sihvola, A. J. Viitanen, I. V. Lindell, and S. A. Tretyakov, Electromagnetic Waves in Chiral and Bi-Isotropic Media. Artech House, 1994.##[16] A. I. Kuznetsov, A. E. Miroshnichenko, Y. Hsing Fu, V. Viswanathan, M. Rahmani, V. Valuckas, Z. Ying Pan, Y. Kivshar, D. S. Pickard, and B. Luk’yanchuk, “Split-ball resonator as a three-dimensional analogue of planar split-rings.,” Nat. Commun., vol. 5, p. 3104, Jan. 2014.##[17] E. Hendry, T. Carpy, J. Johnston, M. Popland, R. V Mikhaylovskiy, a J. Lapthorn, S. M. Kelly, L. D. Barron, N. Gadegaard, and M. Kadodwala, “Ultrasensitive detection and characterization of biomolecules using superchiral fields.,” Nat. Nanotechnol., vol. 5, no. 11, pp. 783–7, Nov. 2010.##[18] S. Yoo, M. Cho, and Q.-H. Park, “Globally enhanced chiral field generation by negative-index metamaterials,” Phys. Rev. B, vol. 89, no. 16, p. 161405, Apr. 2014.##[19] M. a Ordal, R. J. Bell, R. W. Alexander, L. L. Long, and M. R. Querry, “Optical properties of Au, Ni, and Pb at submillimeter wavelengths.,” Appl. Opt., vol. 26, no. 4, pp. 744–52, Feb. 1987.##]
Derivation of Green’s Function for the Interior Region of a Closed Cylinder
Derivation of Green’s Function for the Interior Region of a Closed Cylinder
2
2
The importance of constructing the appropriate Green function to solve a wide range of problems inelectromagnetics and partial differential equations is well-recognized by those dealing with classical electrodynamics and related fields. Although the subject of obtaining the Green function for certain geometries has been extensively studied and addressed in numerous sources, in this paper a systematic method using the Method of Separation of Variables has been employed to scrutinize the Green function with Dirichlet boundary condition for the interior region of a closed cylinder. With further rigorous elaboration, we have demonstrated clearly the path through which the Green function can be accomplished. Additional verifications both in analytical and computer-simulating problems have also been performed to demonstrate the validity of our analysis.
1
The importance of constructing the appropriate Green function to solve a wide range of problems inelectromagnetics and partial differential equations is well-recognized by those dealing with classical electrodynamics and related fields. Although the subject of obtaining the Green function for certain geometries has been extensively studied and addressed in numerous sources, in this paper a systematic method using the Method of Separation of Variables has been employed to scrutinize the Green function with Dirichlet boundary condition for the interior region of a closed cylinder. With further rigorous elaboration, we have demonstrated clearly the path through which the Green function can be accomplished. Additional verifications both in analytical and computer-simulating problems have also been performed to demonstrate the validity of our analysis.
23
33
A.M.
Nezhad Mohammad
A.M.
Nezhad Mohammad
BSc. Student, Department of Electrical Engineering, Amirkabir University of Technology, Tehran, Iran
BSc. Student, Department of Electrical Engineering
Iran
P.
Abdipour
P.
Abdipour
BSc. Student, Department of Electrical Engineering, Amirkabir University of Technology, Tehran, Iran
BSc. Student, Department of Electrical Engineering
Iran
M.
Bababeyg
M.
Bababeyg
BSc. Student, Department of Electrical Engineering, Amirkabir University of Technology, Tehran, Iran
BSc. Student, Department of Electrical Engineering
Iran
H.
Noshad
H.
Noshad
Assistant Professor, Department of Energy Engineering and Physics, Amirkabir University of Technology, Tehran, Iran
Assistant Professor, Department of Energy
Iran
Cylindrical Green’s Function
Electrostatic Potential
Poisson’s Equation.
[Jackson, J.D., “Classical Electrodynamics”, 3rd ed., New York, Wiley, 1999.##Morse P.M., Feshbach H., “Methods of Theoretical Physics”, McGraw-Hill, 1953.##Barton G., “Elements of Green’s functions and propagation: potentials, diffusion, and waves”, Oxford University Press, 1989.##Balanis C.A., “Green’s Functions” in Advanced Engineering Electromagnetics, 2nd ed., Wiley, 2012.##Conway J.T., Cohl S. H., “Exact Fourier expansion in cylindrical coordinates for the three-dimensional Helmholtz Green function”, Journal of Applied Mathematics and Physics, 66, 2009.##Sun J., et al., “Rigorous Green's function formulation for transmembrane potential induced along a 3-D infinite cylindrical cell”, Antennas and Propagation Society International Symposium IEEE, 4: pp. 4076-4079, 2004.##Wu J., Wang C., “An Efficient Method for Intensive Computations of Cylindrical Green's Functions”, Antennas and Propagation Society International Symposium (APSURSI), pp. 2032-2033, 2014##Wu J., Wang C., “Efficient Modeling of Antennas Conformal to Cylindrical Medium Using Cylindrical Green’s Function”, International Symposium on Antennas and Propagation and North American Radio Science Meeting, 2015.##A.Ye. Svezhentsev et al.,” Green’s Functions for Probe-Fed Arbitrary-Shaped Cylindrical Microstrip Antennas”, Antennas and Propagation, IEEE Transaction on, 63: pp. 993-1003, 2015.##Myint-U T., Debnath L., “Linear Partial Differential Equations for Scientists and Engineers”, 4th ed., Birkhauser, 2007.##Arfken G.B., Weber H.J., Harris F.E., “Mathematical Methods for Physicists, A Comprehensive Guide”, 7th ed., Academic Press, 2013.##Abramowitz M., Stegun I.A., “Handbook of Mathematical Functions with Formulas, Graphs, and Mathematical Tables”, Dover Publications, 1972##]
The Transient Behavior of LC and Ring Oscillators under External Frequency Injection
The Transient Behavior of LC and Ring Oscillators under External Frequency Injection
2
2
In this work, time domain analysis is used to solve Adler’s equation in order to obtain the required time, for an oscillator under external injection, reaching the steady-state condition. Mathematical approach has been applied to fully describe the transient of frequency acquisition in injection-locked LC and Ring oscillators considering their time-varying nature. Then, the analysis is verified by simulations of a ring as well as a typical RF-LC oscillator. Likewise, the effect of initial phase difference of injection signal on locking time and phase noise is theoretically studied. For Ring oscillators, a delay-based time–domain and perturbation analysis are used to reveal the dependency of circuit parameters to the locking time. Finally, the design insights are deduced which enable the designers to evaluate and minimize the timing budget required to achieve injection locking in designing a fast locking oscillator. The mathematical consequences in this work explain why there is no transient behavior while ring oscillator signal propagates from a stage to another, or why the initial phase shift of injection signal has no effect on the phase noise of oscillator.
1
In this work, time domain analysis is used to solve Adler’s equation in order to obtain the required time, for an oscillator under external injection, reaching the steady-state condition. Mathematical approach has been applied to fully describe the transient of frequency acquisition in injection-locked LC and Ring oscillators considering their time-varying nature. Then, the analysis is verified by simulations of a ring as well as a typical RF-LC oscillator. Likewise, the effect of initial phase difference of injection signal on locking time and phase noise is theoretically studied. For Ring oscillators, a delay-based time–domain and perturbation analysis are used to reveal the dependency of circuit parameters to the locking time. Finally, the design insights are deduced which enable the designers to evaluate and minimize the timing budget required to achieve injection locking in designing a fast locking oscillator. The mathematical consequences in this work explain why there is no transient behavior while ring oscillator signal propagates from a stage to another, or why the initial phase shift of injection signal has no effect on the phase noise of oscillator.
35
45
A.
Tofangdarzade
A.
Tofangdarzade
PhD Student, Electrical Department of Shahid Beheshti University, Tehran, Iran
PhD Student, Electrical Department of Shahid
Iran
A.
Jalali
A.
Jalali
Assistant professor, Electrical Department of Shahid Beheshti University, Tehran, Iran
Assistant professor, Electrical Department
Iran
Adler’s equation
Time-domain analysis
Injection locking
Oscillator
[Adler, R., “A study of locking phenomena in oscillators”, Proc. IEEE, 61, 1380–1385, 1973.##Kurokawa, K., “Injection locking of microwave solid-state oscillators”, Proc. IEEE, 61, 1336-1410, 1973.##Paciorek, L. j., “Injection locking of oscillators”, Proc. IEEE, 53, 1723-1727, 1965.##Razavi, B., “A study of injection locking and pulling in oscillators”, IEEE J. Solid-state circuits, 39, 1415-1424, 2004.##Maffezzoni, P., “Analysis of Oscillator Injection Locking Through Phase-Domain Impulse-Response”, IEEE Trans. Circuits Syst. I, Reg. Papers, 55, 1297-1305, 2008.##Tong, H., Cheng, S., Karsilayn, A. I., and Martinez, J. S., “An injection-Locked Frequency Divider With Multiple Highly Nonlinear Injection Stages and Large Division Ratios”, IEEE Trans. Circuits Syst. II, Exp. Briefs, 54, 313-317, 2007##Rategh, H. R., and Lee, T. H., “Super Harmonic Injection-Locked Frequency Dividers”, IEEE J. Solid-state circuits. 34, 813-821, 1999.##51, 1989-1993, 2003.##Verma, S., Rategh, H. R., and Lee, T. H., “ A unified model for injection-locked frequency dividers”, IEEE J. Solid-state circuits, 38, 1015-1027, 2003.##Kamogawa, K., Tokumitsu, T., and Aikawa, A., “Injection-locked oscillator chain: A possible solution to millimeter-wave MMIC synthesizers”, IEEE Trans. Microwave Theory Tech., 45, 1578-1584, 1997.##Lyles, U., Copani, T., Bakkaloglu, B., and Kiaei, S., “An Injection- Locked Frequency-Tracking ΣΔ Direct Digital Frequency Synthesizer”, IEEE Trans. Circuits Syst. II, Exp. Briefs, 54, 402-406, 2007.##Chang, H., “Stability Analysis of Self-Injection-Locked oscillators”, IEEE Trans. Microwave Theory Tech.,##Chang, H., “Phase Noise in Self-Injection-Locked Oscillators, Theory and Experiment”, IEEE Trans. Microwave Theory Tech., 51, 1994-1999, 2003.##Chang, H., Cao, X., Mishra, U., and York, R., “Phase noise in coupled oscillators: Theory and experiment”, IEEE Trans. Microwave Theory Tech., vol. 45, pp.604 -615, 1997.##Chang, H., Cao, X., Vaughan, M., Mishra, U., and York, R., “Phase noise in externally injection-locked oscillator arrays”, IEEE Trans. Microwave Theory Tech., vol. 45, pp.2035 -2042, 1997.##Maffezzoni, P., D'Amore, D., “Phase-Noise Reduction in Oscillators via Small-Signal Injection”, IEEE Transactions on Circuits and Systems I: Regular Papers, Volume: 58, Issue: 10, 2498 - 2507, Oct. 2011.##Harjani, R., Lanka, N., and Patnaik, S., “Fast hopping injection locked frequency generation for UWB”, Proc. IEEE Int. Conf. Ultra-WideBand, pp.502 -507, 2007.##Lanka, N., Patnaik, S., and Harjani, R., “Sub-10 ns frequency hopping synthesizer based on injection-locking”, Proc. 38th European Microwave Conf., pp.1581 -1584, 2008.##Lanka, N., Patnaik, S., and Harjani, R., “Frequency-hopped quadrature frequency synthesizer in 0.13 μm technology”, IEEE J. Solid-State Circuits, vol. 46, no. 5, pp.2021 -2032, 2011.##Lanka, N., Patnaik, S., and Harjani, R., “Understanding the transient behavior of injection locked LC oscillators”, Proc. IEEE 2007 Custom Integrated Circuits Conf. (CICC), pp.TP-291 -TP-294, 2007.##Mirzaei, A., Heidari, M., and Abidi, A., “Analysis of oscillators locked by large injection##signals: Generalized Adler's equation and geometrical interpretation”, Proc. IEEE Custom Integrated Circuits Conf. (CICC), pp.737 -740, 2006.##Mirzaei, A., Heidari, M., Bagheri, R., Chehrazi, S., and Abidi, A., “The quadrature LC oscillator: A complete portrait based on injection locking”, IEEE Journal of Solid-State Circuits, vol. 42, pp. 1916-1932, 2007.##Mirzaei, A., Heidari, M., Bagheri, R., Chehrazi, S., and Abidi, A., “Multi-phase injection widens lock range of ring-oscillator-based frequency dividers”, IEEE J. Solid-State Circuits, vol. 43, no. 3, pp.656 -671, 2008.##Saniei, N., Tofangdarzade, A., and Ng, W. T., “Locking Time of Oscillators under External Frequency Injection”, in Proc. IEEE ICEE, 18th Irainian Conference on Electrical Engineering, pp. 391-396, 2010.##Gangasani, G., and Kinget, P., “A time-domain model for predicting the injection locking bandwidth of non-harmonic oscillators”, IEEE Trans. Circuits Syst. II, Exp. Briefs, 53, 1035-1038, 2006.##Leeson, D., “A simple model of feedback oscillator noise spectrum”, Proc. IEEE, vol. 54, no. 2, pp.329 -330, 1966.##Razavi, B., “A study of phase noise in CMOS oscillators”, IEEE J. Solid-State Circuits, vol. 31, no. 3, pp.331-343,1996.##Everard, J., Xu, M., Bale, S., “A Simplified phase noise model for negative-resistance oscillators and a comparison with feedback oscillator models”, IEEE Trans. On Ultrusonics, Ferroelectrics and frequency control. Vo. 59, No. 3, pp. 382-390, 2012.##Hajimiri, A., and Lee, T., “A general theory of phase noise in electrical oscillators”, IEEE J. Solid-State Circuits, vol. 33, no. 2, pp.179 -194, 1998.##Samori, C., Lacaita, A., Villa, F., and Zappa, F., “Spectrum folding and phase noise in LC tuned oscillators”, IEEE Trans. Circuits Syst. II, Analog Digit. Signal Process., vol. 45, no. 7, pp.781 -790, 1998.##Rael, J. and Abidi, A., “Physical processes of phase noise in differential LC oscillators”, Proc. IEEE Custom Integr. Circuits Conf., pp.569 -572, 2000.##Murphy, D., Rael, J., Abidi, A., “Phase noise in LC oscillators: A phasor based analysis of a general result and of loaded Q”, IEEE Transactions on Circuits and Systems I Regular Papers, Volume.57, No. 6, pp. 1187-1203, 2012.##Lee, T., and Hajimiri, A., “Oscillator phase noise: A tutorial”, IEEE J. Solid-State Circuits, vol. 35, no. 3, pp.326 -336, 2000.##Demir, A., Mehrotra, A., Roychowdhury, J., “Phase Noise in oscillators: A unifying theory and numerical methods for characterization”, IEEE Transactions on Circuits and Systems I Fundam. Theory Appl., Volume.47, No. 5, pp. 655-647, 2000##Kalia, S., Elbadry, M., Sadhu, B., Patnaik, S., Qiu, J., Harjani, R., “A simple, unified phase noise model for injection-locked oscillators”, Radio Frequency Integrated Circuits Symposium (RFIC), IEEE, 1 – 4, 2011.##Buonomo, A., Lo Schiavo, A., “Analytical Approach to the Study of Injection-Locked Frequency Dividers”, IEEE Transactions on Circuits and Systems I: Regular Papers, Volume: 60, Issue: 1, 51 – 62, 2013.##]
Decentralized Frequency Restoration in Islanded Converter Base Microgrid
Decentralized Frequency Restoration in Islanded Converter Base Microgrid
2
2
Variation of frequency and voltage by load changes in a microgrid is a challenge in droop control method. Centralized restoration frequency or voltage in a microgrid requires communication link and therefore affects the advantage of decentralized droop control such as reliability, simplicity and inexpensiveness. This paper proposes a decentralized method that restores the frequency of a microgrid without any communication link and maintains these advantages. The method detects signal changing by wavelet transform (WT) to synchronize distributed energy resource (DER) that interfaced by converter to microgrid. Its operation principle and control method are explained and analyzed. The simulation results are presented to validate the effectiveness of the proposed method.
1
Variation of frequency and voltage by load changes in a microgrid is a challenge in droop control method. Centralized restoration frequency or voltage in a microgrid requires communication link and therefore affects the advantage of decentralized droop control such as reliability, simplicity and inexpensiveness. This paper proposes a decentralized method that restores the frequency of a microgrid without any communication link and maintains these advantages. The method detects signal changing by wavelet transform (WT) to synchronize distributed energy resource (DER) that interfaced by converter to microgrid. Its operation principle and control method are explained and analyzed. The simulation results are presented to validate the effectiveness of the proposed method.
47
55
M.
Kosari
M.
Kosari
PhD. Student, Department of Electrical Engineering, Amirkabir University of Technology, Tehran, Iran
PhD. Student, Department of Electrical Engineering
Iran
S. H.
Hosseinian
S. H.
Hosseinian
Professor, Department of Electrical Engineering, Amirkabir University of Technology, Tehran, Iran
Professor, Department of Electrical Engineering,
Iran
A.
Mahmoudi
A.
Mahmoudi
PhD. Student, Department of Electrical Engineering, Amirkabir University of Technology, Tehran, Iran
PhD. Student, Department of Electrical Engineering
Iran
Decentralized Frequency restoration
Droop control
Wavelet transform
[[1] M. C. Chandrokar, D. M. Divan, and R. Adapa, “Control of parallel connected inverters in standalone ac supply systems,” IEEE Trans. Ind.Appl., vol. 29, no. 1, pp. 136–143, Jan./Feb. 1993.##[2] M. C. Chandrokar, D. M. Divan, and B. Banerjee, “Control of distributed ups systems,” in Proc. IEEE Power Electron. Spec. Conf., Jun., 1994,pp. 197–204.##[3] M. N. Marwali, J.-W. Jung, and A. Keyhani, “Control of distributed generation systems—Part II: Load sharing control,” IEEE Trans. PowerElectron., vol. 19, no. 6, pp. 1551–1561, Nov. 2004.##[4] K. D. Brabandere, B. Bolsens, J. V. denKeybus, A. Woyte, J.Driesen, andR. Belmans, “A voltage and frequency droop control method for parallel inverters,” IEEE Trans. Power Electron., vol. 22, no. 4, pp. 1107–1115,Jul. 2007.##[5] E. Barklund, N. Pogaku, M. Prodanovic, C. Hernandez-Aramburo, and T.C. Green, “Energy management in autonomous microgrid using stability constrained droop control of inverters,” IEEE Trans. Power Electron.,vol. 23, no. 5, pp. 2346–2352, Sep. 2008.##[6] D. De and V. Ramanarayanan, “Decentralized parallel operation of inverters sharing unbalanced and nonlinear loads,” IEEE Trans. Power Electron., vol. 25, no. 12, pp. 3015–3025, Dec. 2010.##[7] C. K. Sao and P. W. Lehn, “Autonomous load sharing of voltage source converters,” IEEE Trans. Power Del., vol. 20, no. 2, pp. 1009–1016, Apr.2005.##[8] J. M. Guerrero, L.G. deVicuna, J.Matas,M.Castilla, and J.Miret, “Output impedance design of parallel-connected UPS##inverters with wireless load sharing control,” IEEE Trans. Ind. Electron., vol. 52, no. 4, pp. 1126–1135,Aug. 2005.##[9] Y. W. Li and C. N. Kao, “An accurate power control strategy for power electronics-interfaced distributed generation units operating in a low voltage multibus microgrid,” IEEE Trans. Power Electron., vol. 24, no. 12,pp. 2977–2988, Aug. 2009.##[10] J. He and Y. W. Li, "An enhanced microgrid load demand sharing strategy," IEEE Trans. Power Electron., vol. 27, no. 9, pp. 3984 - 3995, Sep. 2012.##[11] C. T. Lee, C. C. Chu, and P. T. Cheng, "A new droop control method for the autonomous operation of distributed energy resource interface converters," IEEE Trans. Power Electron., vol. 28, no. 4, pp. 1980 - 1993, Apr. 2013.##[12] J. M. Guerrero, J. C. Vasquez, J. Matas, L. G. de Vicuna, and M. Castilla, "Hierarchical control of droop-controlled AC and DC microgrids: A general approach toward standardization," IEEE Trans. Ind. Electron., vol. 58, no. 1, pp. 158–172, Jan. 2011.##[13] A. Bidram and A. Davoudi, "Hierarchical structure of microgrids control system," IEEE Trans. Smart Grid, 2012, vol. 3, no. 4, pp. 1963–1976, Dec. 2012.##[14] Y. A. R. I. Mohamed and A. A. Radwan, "Hierarchical control system for robust microgrid operation and seamless mode transfer in active distribution systems," IEEE Trans. Smart Grid, vol. 2, pp. 352–362, Jun. 2011.##[15] E. A. A. Coelho, P. C. Cortizo, and P. F. D. Garcia, “Small-signal stability for parallel-connected inverters in stand-alone ac supply systems,” IEEE Trans. Ind. Appl., vol. 38, no. 2, pp. 533–542, Mar./Apr. 2002.##[16] N. Pogaku, M. Prodanovic, and T. C. Green, “Modeling, analysis and testing of autonomous operation of an inverter-based microgrid,” IEEE Trans. Power Electron., vol. 22, no. 2, pp. 613–625, Mar. 2007.##[17] E. Barklund, N. Pogaku, M. Prodanovic, C. Hernandez-Aramburo, and T. C. Green, "Energy management in autonomous microgrid using stability-constrained droop control of inverters," IEEE Trans. Power Electron., vol. 23, no. 5, pp. 2346–2352, Sep. 2008.##[18] Y. A.-R. I. Mohamed and E. F. El-Saadany, "Adaptive decentralized droop controller to preserve power sharing stability of paralleled inverters in distributed generation microgrids,"IEEE Trans. Power Electron., vol. 23, no. 6, pp. 2806–2816, Nov. 2008.##[19] S. V. Iyer, M. N. Belur, and M. C. Chandorkar, “A generalized computational method to determine stability of a multi-inverter microgrid,” IEEE Trans. Power Electron., vol. 25, no. 9, pp. 2420–2432, Sep. 2010.##[20] S. G. Mallat, “A theory for multiresolution signal decomposition: The wavelet representation,” IEEE Trans. Pattern Anal. Mach. Intell., vol.1, no. 7, pp. 674–693, Jul. 1989##]
Adaptive Simplified Model Predictive Control with Tuning Considerations
Adaptive Simplified Model Predictive Control with Tuning Considerations
2
2
Model predictive controller is widely used in industrial plants. Uncertainty is one of the critical issues in real systems. In this paper, the direct adaptive Simplified Model Predictive Control (SMPC) is proposed for unknown or time varying plants with uncertainties. By estimating the plant step response in each sample, the controller is designed and the controller coefficients are directly calculated. The proposed method is validated via simulations for both slow and fast time varying systems. Simulation results indicate the controller ability for tracking references in the presence of plant’s time varying parameters. In addition, an analytical tuning method for adjusting prediction horizon is proposed based on optimization of the objective function. It leads to a simple formula including the model parameters, and an indirect adaptive controller can be designed based on the analytical formula. Simulation results indicate a better performance for the tuned controller. Finally, experimental tests are performed to show the effectiveness of the proposed methodologies.
1
Model predictive controller is widely used in industrial plants. Uncertainty is one of the critical issues in real systems. In this paper, the direct adaptive Simplified Model Predictive Control (SMPC) is proposed for unknown or time varying plants with uncertainties. By estimating the plant step response in each sample, the controller is designed and the controller coefficients are directly calculated. The proposed method is validated via simulations for both slow and fast time varying systems. Simulation results indicate the controller ability for tracking references in the presence of plant’s time varying parameters. In addition, an analytical tuning method for adjusting prediction horizon is proposed based on optimization of the objective function. It leads to a simple formula including the model parameters, and an indirect adaptive controller can be designed based on the analytical formula. Simulation results indicate a better performance for the tuned controller. Finally, experimental tests are performed to show the effectiveness of the proposed methodologies.
57
63
A.S.
Ashtari
A.S.
Ashtari
MSc. Student, APAC Research Group, Industrial Control Center of Excellence, K.N.Toosi University of Technology, Tehran, Iran
MSc. Student, APAC Research Group, Industrial
Iran
A.
Khaki Sedigh
A.
Khaki Sedigh
Professor, APAC Research Group, Industrial Control Center of Excellence, K.N.Toosi University of Technology, Tehran, Iran
Professor, APAC Research Group, Industrial
Iran
Adaptive Model Predective Control
Simplified Model Predective Control
Tunning
[[1] Richalet, J. (1993). Industrial applications of model based predictive control. Automatica, 29(5), 1251-1274.##[2] Qin, S. J., & Badgwell, T. A. (2003). A survey of industrial model predictive control technology. Control engineering practice, 11(7), 733-764.##[3] Morari, M., & Lee, J. H. (1999). Model predictive control: past, present and future. Computers & Chemical Engineering, 23(4), 667-682.##[4] Cutler, C. R., & Ramaker, B. L. (1980, August). Dynamic matrix control-a computer control algorithm. In Proceedings of the joint automatic control conference (Vol. 1, pp. Wp5-B). Piscataway, NJ: American Automatic Control Council.##[5] Gupta, Y. P. (1993). A simplified predictive control approach for handling constraints through linear programming. Computers in industry, 21(3), 255-265.##[6] Abou-Jeyab, R. A., Gupta, Y. P., Gervais, J. R., Branchi, P. A., & Woo, S. S. (2001). Constrained multivariable control of a distillation column using a simplified model predictive control algorithm. Journal of Process Control, 11(5), 509-517.##[7] Abou-Jeyab, R. A., & Gupta, Y. P. (2001). Constrained multivariable control of fluidized catalytic cracking process using linear programming. Chemical Engineering Research and Design, 79(3), 274-282.##[8] Gupta, Y. P. (1993). Characteristic equations and robust stability of a simplified predictive control algorithm. The Canadian Journal of Chemical Engineering, 71(4), 617-624.##[9] Fukushima, H., Kim, T. H., & Sugie, T. (2007). Adaptive model predictive control for a class of constrained linear systems based on the comparison model. Automatica, 43(2), 301-308.##[10] Kim, J. S. (2010, October). Recent advances in adaptive MPC. In Proceedings of the International Conference on Control Automation and Systems (pp. 218-222). ##[11] Kim, J. S., Yoon, T. W., Shim, H., & Seo, J. H. (2008). Switching adaptive output feedback model predictive control for a class of input-constrained linear plants. IET Control Theory & Applications, 2(7), 573-582.##[12] Bagheri, P., Khaki Sedigh, A. (2013). Analytical approach to tuning of model predictive control for first-order plus dead time models. IET Control Theory & Applications, 7(14), 1806-1817.##[13] Bagheri, P., Khaki-Sedigh, A. (2010). An ANOVA Based Analytical Dynamic Matrix Controller Tuning Procedure for FOPDT Models. Amirkabir International Journal of Modeling, Identification, Simulation and Control, Vol. 42, No. 2.##]