Self-tuning digital controllers for servo systems

Adaptive self-tuning systems have been the subject of a great deal of research effort in recent years. Practical applications have lagged behind such work, in the main being applied in the process industries. Few serve applications have been reported, the wide bandwidths and demanding performance specifications raising problems not found in the process world. The research project described here is concerned with the use of self-tuning digital controllers applied to servo systems, specifically an electro-mechanical actuation unit. Practical limitations, such as stiction, friction and velocity saturation effects are taken into account. [Continues.

Column-row addressing of thermo-optic phase shifters for controlling large silicon photonic circuits

We demonstrate a time-multiplexed row-column addressing scheme to drive thermo-optic phase shifters in a silicon photonic circuit. By integrating a diode in series with the heater, we can connect $N \times M$ heaters in an matrix topology to $N$ row and $M$ column lines. The heaters are digitally driven with pulse-width modulation, and time-multiplexed over different channels. This makes it possible to drive the circuit without digital-to-analog converters, and using only $M+N$ wires. We demonstrate this concept with a $1 \times 16$ power splitter tree with 15 thermo-optic phase shifters that are controlled in a $3 \times 5$ matrix, connected through 8 bond pads. This technique is especially useful in silicon photonic circuits with many tuners but limited space for electrical connections

Self-tuning controllers via the state space

Imperial Users onl

Automatic guitar tuner

The present work consists in the design of a guitar tuner system. The proposed system automatically measures the initial musical tone and rotates the tuner system of the instrument to achieve the right tone for the selected strin

Multipurpose silicon photonics signal processor core

[EN] Integrated photonics changes the scaling laws of information and communication systems offering architectural choices that combine photonics with electronics to optimize performance, power, footprint, and cost. Application-specific photonic integrated circuits, where particular circuits/chips are designed to optimally perform particular functionalities, require a considerable number of design and fabrication iterations leading to long development times. A different approach inspired by electronic Field Programmable Gate Arrays is the programmable photonic processor, where a common hardware implemented by a two-dimensional photonic waveguide mesh realizes different functionalities through programming. Here, we report the demonstration of such reconfigurable waveguide mesh in silicon. We demonstrate over 20 different functionalities with a simple seven hexagonal cell structure, which can be applied to different fields including communications, chemical and biomedical sensing, signal processing, multiprocessor networks, and quantum information systems. Our work is an important step toward this paradigm.J.C. acknowledges funding from the ERC Advanced Grant ERC-ADG-2016-741415 UMWP-Chip, I.G. acknowledges the funding through the Spanish MINECO Ramon y Cajal program. D.P. acknowledges financial support from the UPV through the FPI predoctoral funding scheme. D.J.T. acknowledges funding from the Royal Society for his University Research Fellowship.Pérez-López, D.; Gasulla Mestre, I.; Crudgington, L.; Thomson, DJ.; Khokhar, AZ.; Li, K.; Cao, W.... (2017). Multipurpose silicon photonics signal processor core. Nature Communications. 8(1925):1-9. https://doi.org/10.1038/s41467-017-00714-1S1981925Doerr, C. R. & Okamoto, K. Advances in silica planar lightwave circuits. J. Lightw. Technol. 24, 4763–4789 (2006).Coldren, L. A. et al. High performance InP-based photonic ICs—A tutorial. J. Lightw. Technol 29, 554–570 (2011).Soref, R. The past, present, and future of silicon photonics. IEEE J. Sel. Top. Quantum Electron. 12, 1678–1687 (2006).Bogaerts, W. Design challenges in silicon photonics. IEEE J. Sel. Top. Quantum Electron. 20, 8202008 (2014).Bogaerts, W. et al. Nanophotonic waveguides in silicon-on-insulator fabricated with CMOS technology. J. Lightw. Technol. 23, 401–412 (2005).Smit, M. K. et al. An introduction to InP-based generic integration technology. Semicond. Sci. Technol. 29, 083001 (2014).Leinse, A. et al. TriPleX waveguide platform: low-loss technology over a wide wavelength range. Proc. SPIE 8767, 87670E (2013).Kish, F. et al. From visible light-emitting diodes to large-scale III–V photonic integrated circuits. Proc. IEEE 101, 2255–2270 (2013).Heck, M. J. R. et al. Hybrid silicon photonic integrated circuit technology. IEEE J. Sel. Top. Quantum Electron. 19, 6100117 (2013).Sacher, W. et al. Multilayer silicon nitride-on-silicon integrated photonic platforms and devices. J. Lightw. Technol. 33, 901–910 (2015).Asghari, M. Silicon photonics: A low cost integration platform for datacom and telecom applications. In OFC/NFOEC 2008 – 2008 Conference on Optical Fiber Communication/National Fiber Optic Engineers Conference 1–10 (San Diego, USA, 2008).Melati, D. et al. Integrated all-optical MIMO demultiplexer for mode- and wavelength-division-multiplexed transmission. Opt. Lett. 42, 342–345 (2017).Waterhouse, R. & Novak, D. Realizing 5G: microwave photonics for 5G mobile wireless systems. IEEE Microw. Mag. 16, 84–92 (2015).Marpaung, D. et al. Integrated microwave photonics. Laser Photon. Rev. 7, 506–538 (2013).Iezekiel, S., Burla, M., Klamkin, J., Marpaung, D. & Capmany, J. RF engineering meets optoelectronics: Progress in integrated microwave photonics. IEEE Microw. Mag. 16, 28–45 (2015).Technology focus on microwave photonics. Nat. Photon. 5, 723 (2011).Ghelfi, P. et al. A fully photonics-based coherent radar system. Nature 507, 341–345 (2014).Heideman, R. G. TriPleX™-based integrated optical ring resonators for lab-ona-chip-and environmental detection. IEEE J. Sel. Top. Quantum Electron. 18, 1583–1596 (2012).Estevez, M. C., Alvarez, M. & Lechuga, L. Integrated optical devices for lab-on-a-chip biosensing applications. Laser Photon. Rev. 6, 463–487 (2012).Almeida, V. R., Barrios, C. A., Panepucci, R. & Lipson, M. All-optical control of light on a silicon chip. Nature 431, 1081–1084 (2004).Norberg, E. J., Guzzon, R. S., Parker, J. S., Johansson, L. A. & Coldren, L. A. Programmable photonic microwave filters monolithically integrated in InP/InGaAsP. J. Lightw. Technol. 29, 1611–1619 (2011).Wang, J. et al. Reconfigurable radio-frequency arbitrary waveforms synthesized in a silicon photonic chip. Nat. Commun. 6, 5957 (2015).Hill, M. T. et al. A fast low power optical memory based on coupled micro-ring lasers. Nature 432, 206–209 (2004).Slavík, R. et al. Photonic temporal integrator for all-optical computing. Opt. Express 16, 18202–18214 (2008).Sun, C. et al. A monolithically-integrated chip-to-chip optical link in bulk CMOS. IEEE J. Solid-State Circ. 50, 828–844 (2015).Sun, C. et al. Single-chip microprocessor that communicates directly using light. Nature 528, 534–538 (2015).Assefa, S. et al. in Optical Fibre Communication Conference OMM6, https://www.osapublishing.org/abstract.cfm?uri=OFC-2011-OMM6 (Optical Society of America, 2011).Peruzzo, A. et al. Multimode quantum interference of photons in multiport integrated devices. Nat. Commun. 2, 224 (2011).Bonneau, D. et al. Quantum interference and manipulation of entanglement in silicon wire waveguide quantum circuits. N. J. Phys. 14, 045003 (2012).Metcalf, B. J. et al. Multiphoton quantum interference in a multiport integrated photonic device. Nat. Commun. 4, 1356 (2013).Muñoz, P. et al. in 16th International Conference on Transparent Optical Networks (ICTON), 1–4 (Graz, 2014).Ribeiro, A. et al. Demonstration of a 4×4-port universal linear circuit. Optica 3, 1348–1357 (2016).Liu, W. et al. A fully reconfigurable photonic integrated signal processor. Nat. Photon 10, 190–195 (2016).Graydon, O. Birth of the programmable optical chip. Nat. Photon 10, 1 (2016).Pérez, D., Gasulla, I. & Capmany, J. Software-defined reconfigurable microwave photonics processor. Opt. Express 23, 14640–14654 (2015).Miller, D. A. B. Self-configuring universal linear optical component. Photon. Res. 1, 1–15 (2013).Miller, D. A. B. Self-aligning universal beam coupler. Opt. Express 21, 6360–6370 (2013).Clements, W. R. et al. Optimal design for universal multiport interferometers. Optica 3, 1460–1465 (2016).Zhuang, L., Roeloffzen, C. G. H., Hoekman, M., Boller, K.-J. & Lowery, A. J. Programmable photonic signal processor chip for radiofrequency applications. Optica 2, 854–859 (2015).Capmany, J., Gasulla, I. & Pérez, D. Microwave photonics: The programmable processor. Nat. Photon. 10, 6–8 (2016).Pérez, D., Gasulla., Capmany, J. & Soref, R. A. Reconfigurable lattice mesh designs for programmable photonic processors. Opt. Express 24, 12093–12106 (2016).Madsen, C. K. & Zhao, J. H. Optical Filter Design and Analysis: A Signal Processing Approach. 1st edn. (Wiley, 1999).Jinguji, K. Synthesis of coherent two-port lattice-form optical delay-line circuit. J. Lightw. Technol. 13, 73–82 (1995).Jinguji, K. Synthesis of coherent two-port Optical delay-line circuit with ring waveguides. J. Lightw. Technol. 14, 1882–1898 (1996).Madsen, C. K. General IIR optical filter design for WDM applications using all-pass filters. J. Lightw. Technol. 18, 860–868 (2000).Burla, M. et al. On-chip CMOS compatible reconfigurable optical delay line with separate carrier tuning for microwave photonic signal processing. Opt. Express 19, 21475–21484 (2011).Yariv, A. et al. Coupled resonator optical waveguides: a proposal and analysis. Opt. Lett. 24, 711–713 (1999).Hebner, J. E. et al. Distributed and localized feedback in microresonator sequences for linear and nonlinear optics. J. Opt. Soc. Am. B. 21, 1665–1673 (2004).Fandiño, J. S. et al. A monolithic integrated photonic microwave filter. Nat. Photon. 11, 124–129 (2017).Miller, D. A. B. All linear optical devices are mode converters. Opt. Express 20, 23985–23993 (2012).Reck, M. et al. Experimental realization of any discrete unitary operator. Phys. Rev. Lett. 73, 58–61 (1994).Carolan, J. et al. Universal linear optics. Science 349, 711 (2015).Nielsen, M. A. & Chuang, I. L. Quantum Computation and Quantum Information. 1st edn. (Cambridge University Press, 2001).Miller, D. A. B. Perfect optics with imperfect components. Optica 2, 747–750 (2015).Grillanda, S. et al. Non-invasive monitoring and control in silicon photonics using CMOS integrated electronics. Optica 1, 129–136 (2014)

Doubly-fed induction generator used in wind energy

Wound-rotor induction generator has numerous advantages in wind power generation over other generators. One scheme for wound-rotor induction generator is realized when a converter cascade is used between the slip-ring terminals and the utility grid to control the rotor power. This configuration is called the doubly-fed induction generator (DFIG). In this work, a novel induction machine model is developed. This model includes the saturation in the main and leakage flux paths. It shows that the model which considers the saturation effects gives more realistic results. A new technique, which was developed for synchronous machines, was applied to experimentally measure the stator and rotor leakage inductance saturation characteristics on the induction machine. A vector control scheme is developed to control the rotor side voltage-source converter. Vector control allows decoupled or independent control of both active and reactive power of DFIG. These techniques are based on the theory of controlling the B- and q- axes components of voltage or current in different reference frames. In this work, the stator flux oriented rotor current control, with decoupled control of active and reactive power, is adopted. This scheme allows the independent control of the generated active and reactive power as well as the rotor speed to track the maximum wind power point. Conventionally, the controller type used in vector controllers is of the PI type with a fixed proportional and integral gain. In this work, different intelligent schemes by which the controller can change its behavior are proposed. The first scheme is an adaptive gain scheduler which utilizes different characteristics to generate the variation in the proportional and the integral gains. The second scheme is a fuzzy logic gain scheduler and the third is a neuro-fuzzy controller. The transient responses using the above mentioned schemes are compared analytically and experimentally. It has been found that although the fuzzy logic and neuro-fuzzy schemes are more complicated and have many parameters; this complication provides a higher degree of freedom in tuning the controller which is evident in giving much better system performance. Finally, the simulation results were experimentally verified by building the experimental setup and implementing the developed control schemes