Quasi-optical power combining using mutually synchronized oscillator arrays

York, R.A.; Compton, R.C.

doi:10.1109/22.81670

Cited by 226 publications

(59 citation statements)

References 23 publications

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“…Technological applications of the coupled oscillator model (1) and its generalization (4) include deep brain stimulation (Tass, 2003;Nabi and Moehlis, 2011;Franci et al, 2012), locking in solid-state circuit oscillators (Abidi and Chua, 1979;Mirzaei et al, 2007), planar vehicle coordination Sepulchre et al, 2007Sepulchre et al, , 2008Klein, 2008;Klein et al, 2008), carrier synchronization without phase-locked loops (Rahman et al, 2011), synchronization in semiconductor laser arrays (Kozyreff et al, 2000), and microwave oscillator arrays (York and Compton, 2002). Since alternating current (AC) circuits are naturally modeled by equations similar to (1), some electric applications are found in structure-preserving (Bergen and Hill, 1981;Sauer and Pai, 1998) and networkreduced power system models (Chiang et al, 1995;Dörfler and Bullo, 2012b), and droop-controlled inverters in microgrids (Simpson-Porco et al, 2013).…”

Section: Applications In Engineeringmentioning

confidence: 99%

Synchronization in complex networks of phase oscillators: A survey

2014

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The emergence of synchronization in a network of coupled oscillators is a fascinating subject of multidisciplinary research. This survey reviews the vast literature on the theory and the applications of complex oscillator networks. We focus on phase oscillator models that are widespread in real-world synchronization phenomena, that generalize the celebrated Kuramoto model, and that feature a rich phenomenology. We review the history and the countless applications of this model throughout science and engineering. We justify the importance of the widespread coupled oscillator model as a locally canonical model and describe some selected applications relevant to control scientists, including vehicle coordination, electric power networks, and clock synchronization. We introduce the reader to several synchronization notions and performance estimates. We propose analysis approaches to phase and frequency synchronization, phase balancing, pattern formation, and partial synchronization. We present the sharpest known results about synchronization in networks of homogeneous and heterogeneous oscillators, with complete or sparse interconnection topologies, and in finite-dimensional and infinite-dimensional settings. We conclude by summarizing the limitations of existing analysis methods and by highlighting some directions for future research.

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Section: Applications In Engineeringmentioning

confidence: 99%

Synchronization in complex networks of phase oscillators: A survey

2014

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“…Biological examples include networks of pacemaker cells in the heart [14,15]; circadian pacemaker cells in the suprachiasmatic nucleus of the brain (where the individual cellular frequencies have recently been measured for the first time [16]); metabolic synchrony in yeast cell suspensions [17,18]; congregations of synchronously flashing fireflies [19,20]; and crickets that chirp in unison [21]. There are also many examples in physics and engineering, from arrays of lasers [22,23] and microwave oscillators [24] to superconducting Josephson junctions [25,26].…”

Section: Introductionmentioning

confidence: 99%

From Kuramoto to Crawford: exploring the onset of synchronization in populations of coupled oscillators

Strogatz

2000

Physica D: Nonlinear Phenomena

2,685

2,342

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The Kuramoto model describes a large population of coupled limit-cycle oscillators whose natural frequencies are drawn from some prescribed distribution. If the coupling strength exceeds a certain threshold, the system exhibits a phase transition: some of the oscillators spontaneously synchronize, while others remain incoherent. The mathematical analysis of this bifurcation has proved both problematic and fascinating. We review 25 years of research on the Kuramoto model, highlighting the false turns as well as the successes, but mainly following the trail leading from Kuramoto's work to Crawford's recent contributions. It is a lovely winding road, with excursions through mathematical biology, statistical physics, kinetic theory, bifurcation theory, and plasma physics.

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“…Each coupling object holds information such as the distance between active elements. The values of the time delay and coupling are computed by the coupling object from equations (9) and (11). When an active antenna object computes its new value at each time step, it interrogates each of its neighbouring elements and the associated coupling object to obtain the appropriate time-delayed value; this value is then attenuated in order to account for free space loss.…”

Section: Time Domain Computer Simulation Of An Active Antenna Chain Amentioning

confidence: 99%