Distributed adaptive signal processing for frequency estimation

It is widely recognised that future smart grids will heavily rely upon intelligent communication and signal processing as enabling technologies for their operation. Traditional tools for power system analysis, which have been built from a circuit theory perspective, are a good match for balanced system conditions. However, the unprecedented changes that are imposed by smart grid requirements, are pushing the limits of these old paradigms. To this end, we provide new signal processing perspectives to address some fundamental operations in power systems such as frequency estimation, regulation and fault detection. Firstly, motivated by our finding that any excursion from nominal power system conditions results in a degree of non-circularity in the measured variables, we cast the frequency estimation problem into a distributed estimation framework for noncircular complex random variables. Next, we derive the required next generation widely linear, frequency estimators which incorporate the so-called augmented data statistics and cater for the noncircularity and a widely linear nature of system functions. Uniquely, we also show that by virtue of augmented complex statistics, it is possible to treat frequency tracking and fault detection in a unified way. To address the ever shortening time-scales in future frequency regulation tasks, the developed distributed widely linear frequency estimators are equipped with the ability to compensate for the fewer available temporal voltage data by exploiting spatial diversity in wide area measurements. This contribution is further supported by new physically meaningful theoretical results on the statistical behavior of distributed adaptive filters. Our approach avoids the current restrictive assumptions routinely employed to simplify the analysis by making use of the collaborative learning strategies of distributed agents. The efficacy of the proposed distributed frequency estimators over standard strictly linear and stand-alone algorithms is illustrated in case studies over synthetic and real-world three-phase measurements. An overarching theme in this thesis is the elucidation of underlying commonalities between different methodologies employed in classical power engineering and signal processing. By revisiting fundamental power system ideas within the framework of augmented complex statistics, we provide a physically meaningful signal processing perspective of three-phase transforms and reveal their intimate connections with spatial discrete Fourier transform (DFT), optimal dimensionality reduction and frequency demodulation techniques. Moreover, under the widely linear framework, we also show that the two most widely used frequency estimators in the power grid are in fact special cases of frequency demodulation techniques. Finally, revisiting classic estimation problems in power engineering through the lens of non-circular complex estimation has made it possible to develop a new self-stabilising adaptive three-phase transformation which enables algorithms designed for balanced operating conditions to be straightforwardly implemented in a variety of real-world unbalanced operating conditions. This thesis therefore aims to help bridge the gap between signal processing and power communities by providing power system designers with advanced estimation algorithms and modern physically meaningful interpretations of key power engineering paradigms in order to match the dynamic and decentralised nature of the smart grid.Open Acces

Cavity Field Control for Linear Particle Accelerators

High-energy linear particle accelerators enable exploration of the microscopic structure of pharmaceuticals, solar cells, fuel cells, high-temperature superconductors, and the universe itself. These accelerators accelerate charged particles using oscillating magnetic fields that are confined in metal cavities. The amplitudes and phases of the electromagnetic fields need to be accurately controlled by fast feedback loops for proper accelerator operation.This thesis is based on the author's work on performance analysis and control design for the field control loops of the linear accelerator at the European Spallation Source (ESS), a neutron microscope that is under construction in Lund, Sweden. The main contribution of the thesis is a comprehensive treatment of the field control problem during flat-top, which gives more insight into the control aspects than previous work. The thesis demonstrates that a key to understand the dynamics of the field control loop is to represent it as a single-input single-output system with complex coefficients. This representation is not new itself but has seen limited use for field control analysis.The thesis starts by developing practical and theoretical tools for analysis and control design for complex-coefficients systems. This is followed by two main parts on cavity field control. The first part introduces parametrizations that enable a better understanding of the cavity dynamics and discusses the most essential aspects of cavity field control. The second part builds on the first one and treats a selection of more advanced topics that all benefit from the complex-coefficient representation: analysis of a polar controller structure, field control design in the presence of parasitic cavity resonances, digital downconversion for low-latency feedback, energy-optimal excitation of accelerating cavities, and an intuitive design method for narrowband disturbance rejection. The results of the investigations in this thesis provide a better understanding of the field control problem and have influenced the design of the field controllers at ESS

Long Stroke FTS

Thesis (Ph. D.)--Massachusetts Institute of Technology, Dept. of Mechanical Engineering, 2005.Includes bibliographical references (p. 375-384).In this thesis, I detail the design and control of a linear long stroke fast tool servo (FTS) with integral balance mass. The long stroke fast tool servo consists of an air bearing stage driven by a unique three phase oil cooled linear motor. The linear FTS has a travel range of 25 mm and is capable of 100 m/s² accelerations. The FTS is mounted to a T-base diamond turning machine (DTM). The FTS is attached to a hydrostatic bearing supported in-feed stage which is driven by a second linear motor. The in-feed stage is allowed to move in response to the FTS actuation forces and thus acts as an integral balance mass. We have developed a unique control structure to control the position of both the FTS and the reaction mass. The FTS controller employs a conventional lead-lag inner loop, an adaptive feedforward cancelation (AFC) outer loop, and command pre-shifting. For the FTS controller, the AFC resonators are placed in the forward path which creates infinite gain at the resonator frequency. The controller for the hydrostatic stage consists of a conventional lead-lag control inner-loop and a base acceleration feedback controller. The acceleration feedback controller consists of a high-pass filter, a double integrator for phase compensation, and an array of AFC resonators. For the base acceleration controller, the AFC resonators are placed in the feedback path and thus act as narrow-frequency notch filters. The notch filters allow the hydrostatic stage/balance mass to move freely at the commanded trajectory harmonics thus attenuating the forces introduced into the DTM. The AFC control loops are designed using a new loop shaping perspective for AFC control. In this thesis, we present two extensions to AFC control.(cont.) The first extension called Oscillator Amplitude Control (OAC) is used to approximate the convergence characteristics of an AFC controller. The second extension termed Amplitude Modulated Adaptive Feedforward Cancelation (AMAFC) is designed to exactly cancel disturbances with a time varying amplitude.by Marten F. Byl.Ph.D