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- All Subjects: Electrical Engineering
- Genre: Doctoral Dissertation
- Member of: Theses and Dissertations
Description
Traditional approaches to modeling microgrids include the behavior of each inverter operating in a particular network configuration and at a particular operating point. Such models quickly become computationally intensive for large systems. Similarly, traditional approaches to control do not use advanced methodologies and suffer from poor performance and limited operating range. In this document a linear model is derived for an inverter connected to the Thevenin equivalent of a microgrid. This model is then compared to a nonlinear simulation model and analyzed using the open and closed loop systems in both the time and frequency domains. The modeling error is quantified with emphasis on its use for controller design purposes. Control design examples are given using a Glover McFarlane controller, gain sched- uled Glover McFarlane controller, and bumpless transfer controller which are compared to the standard droop control approach. These examples serve as a guide to illustrate the use of multi-variable modeling techniques in the context of robust controller design and show that gain scheduled MIMO control techniques can extend the operating range of a microgrid. A hardware implementation is used to compare constant gain droop controllers with Glover McFarlane controllers and shows a clear advantage of the Glover McFarlane approach.
ContributorsSteenis, Joel (Author) / Ayyanar, Raja (Thesis advisor) / Mittelmann, Hans (Committee member) / Tsakalis, Konstantinos (Committee member) / Tylavsky, Daniel (Committee member) / Arizona State University (Publisher)
Created2013
Description
The Kuramoto model is an archetypal model for studying synchronization in groups
of nonidentical oscillators where oscillators are imbued with their own frequency and
coupled with other oscillators though a network of interactions. As the coupling
strength increases, there is a bifurcation to complete synchronization where all oscillators
move with the same frequency and show a collective rhythm. Kuramoto-like
dynamics are considered a relevant model for instabilities of the AC-power grid which
operates in synchrony under standard conditions but exhibits, in a state of failure,
segmentation of the grid into desynchronized clusters.
In this dissertation the minimum coupling strength required to ensure total frequency
synchronization in a Kuramoto system, called the critical coupling, is investigated.
For coupling strength below the critical coupling, clusters of oscillators form
where oscillators within a cluster are on average oscillating with the same long-term
frequency. A unified order parameter based approach is developed to create approximations
of the critical coupling. Some of the new approximations provide strict lower
bounds for the critical coupling. In addition, these approximations allow for predictions
of the partially synchronized clusters that emerge in the bifurcation from the
synchronized state.
Merging the order parameter approach with graph theoretical concepts leads to a
characterization of this bifurcation as a weighted graph partitioning problem on an
arbitrary networks which then leads to an optimization problem that can efficiently
estimate the partially synchronized clusters. Numerical experiments on random Kuramoto
systems show the high accuracy of these methods. An interpretation of the
methods in the context of power systems is provided.
of nonidentical oscillators where oscillators are imbued with their own frequency and
coupled with other oscillators though a network of interactions. As the coupling
strength increases, there is a bifurcation to complete synchronization where all oscillators
move with the same frequency and show a collective rhythm. Kuramoto-like
dynamics are considered a relevant model for instabilities of the AC-power grid which
operates in synchrony under standard conditions but exhibits, in a state of failure,
segmentation of the grid into desynchronized clusters.
In this dissertation the minimum coupling strength required to ensure total frequency
synchronization in a Kuramoto system, called the critical coupling, is investigated.
For coupling strength below the critical coupling, clusters of oscillators form
where oscillators within a cluster are on average oscillating with the same long-term
frequency. A unified order parameter based approach is developed to create approximations
of the critical coupling. Some of the new approximations provide strict lower
bounds for the critical coupling. In addition, these approximations allow for predictions
of the partially synchronized clusters that emerge in the bifurcation from the
synchronized state.
Merging the order parameter approach with graph theoretical concepts leads to a
characterization of this bifurcation as a weighted graph partitioning problem on an
arbitrary networks which then leads to an optimization problem that can efficiently
estimate the partially synchronized clusters. Numerical experiments on random Kuramoto
systems show the high accuracy of these methods. An interpretation of the
methods in the context of power systems is provided.
ContributorsGilg, Brady (Author) / Armbruster, Dieter (Thesis advisor) / Mittelmann, Hans (Committee member) / Scaglione, Anna (Committee member) / Strogatz, Steven (Committee member) / Welfert, Bruno (Committee member) / Arizona State University (Publisher)
Created2018
Description
In this dissertation, two problems are addressed in the verification and control of Cyber-Physical Systems (CPS):
1) Falsification: given a CPS, and a property of interest that the CPS must satisfy under all allowed operating conditions, does the CPS violate, i.e. falsify, the property?
2) Conformance testing: given a model of a CPS, and an implementation of that CPS on an embedded platform, how can we characterize the properties satisfied by the implementation, given the properties satisfied by the model?
Both problems arise in the context of Model-Based Design (MBD) of CPS: in MBD, the designers start from a set of formal requirements that the system-to-be-designed must satisfy.
A first model of the system is created.
Because it may not be possible to formally verify the CPS model against the requirements, falsification tries to verify whether the model satisfies the requirements by searching for behavior that violates them.
In the first part of this dissertation, I present improved methods for finding falsifying behaviors of CPS when properties are expressed in Metric Temporal Logic (MTL).
These methods leverage the notion of robust semantics of MTL formulae: if a falsifier exists, it is in the neighborhood of local minimizers of the robustness function.
The proposed algorithms compute descent directions of the robustness function in the space of initial conditions and input signals, and provably converge to local minima of the robustness function.
The initial model of the CPS is then iteratively refined by modeling previously ignored phenomena, adding more functionality, etc., with each refinement resulting in a new model.
Many of the refinements in the MBD process described above do not provide an a priori guaranteed relation between the successive models.
Thus, the second problem above arises: how to quantify the distance between two successive models M_n and M_{n+1}?
If M_n has been verified to satisfy the specification, can it be guaranteed that M_{n+1} also satisfies the same, or some closely related, specification?
This dissertation answers both questions for a general class of CPS, and properties expressed in MTL.
1) Falsification: given a CPS, and a property of interest that the CPS must satisfy under all allowed operating conditions, does the CPS violate, i.e. falsify, the property?
2) Conformance testing: given a model of a CPS, and an implementation of that CPS on an embedded platform, how can we characterize the properties satisfied by the implementation, given the properties satisfied by the model?
Both problems arise in the context of Model-Based Design (MBD) of CPS: in MBD, the designers start from a set of formal requirements that the system-to-be-designed must satisfy.
A first model of the system is created.
Because it may not be possible to formally verify the CPS model against the requirements, falsification tries to verify whether the model satisfies the requirements by searching for behavior that violates them.
In the first part of this dissertation, I present improved methods for finding falsifying behaviors of CPS when properties are expressed in Metric Temporal Logic (MTL).
These methods leverage the notion of robust semantics of MTL formulae: if a falsifier exists, it is in the neighborhood of local minimizers of the robustness function.
The proposed algorithms compute descent directions of the robustness function in the space of initial conditions and input signals, and provably converge to local minima of the robustness function.
The initial model of the CPS is then iteratively refined by modeling previously ignored phenomena, adding more functionality, etc., with each refinement resulting in a new model.
Many of the refinements in the MBD process described above do not provide an a priori guaranteed relation between the successive models.
Thus, the second problem above arises: how to quantify the distance between two successive models M_n and M_{n+1}?
If M_n has been verified to satisfy the specification, can it be guaranteed that M_{n+1} also satisfies the same, or some closely related, specification?
This dissertation answers both questions for a general class of CPS, and properties expressed in MTL.
ContributorsAbbas, Houssam Y (Author) / Fainekos, Georgios (Thesis advisor) / Duman, Tolga (Thesis advisor) / Mittelmann, Hans (Committee member) / Tsakalis, Konstantinos (Committee member) / Arizona State University (Publisher)
Created2015
Description
For the last 50 years, oscillator modeling in ranging systems has received considerable
attention. Many components in a navigation system, such as the master oscillator
driving the receiver system, as well the master oscillator in the transmitting system
contribute significantly to timing errors. Algorithms in the navigation processor must
be able to predict and compensate such errors to achieve a specified accuracy. While
much work has been done on the fundamentals of these problems, the thinking on said
problems has not progressed. On the hardware end, the designers of local oscillators
focus on synthesized frequency and loop noise bandwidth. This does nothing to
mitigate, or reduce frequency stability degradation in band. Similarly, there are not
systematic methods to accommodate phase and frequency anomalies such as clock
jumps. Phase locked loops are fundamentally control systems, and while control
theory has had significant advancement over the last 30 years, the design of timekeeping
sources has not advanced beyond classical control. On the software end,
single or two state oscillator models are typically embedded in a Kalman Filter to
alleviate time errors between the transmitter and receiver clock. Such models are
appropriate for short term time accuracy, but insufficient for long term time accuracy.
Additionally, flicker frequency noise may be present in oscillators, and it presents
mathematical modeling complications. This work proposes novel H∞ control methods
to address the shortcomings in the standard design of time-keeping phase locked loops.
Such methods allow the designer to address frequency stability degradation as well
as high phase/frequency dynamics. Additionally, finite-dimensional approximants of
flicker frequency noise that are more representative of the truth system than the
tradition Gauss Markov approach are derived. Last, to maintain timing accuracy in
a wide variety of operating environments, novel Banks of Adaptive Extended Kalman
Filters are used to address both stochastic and dynamic uncertainty.
attention. Many components in a navigation system, such as the master oscillator
driving the receiver system, as well the master oscillator in the transmitting system
contribute significantly to timing errors. Algorithms in the navigation processor must
be able to predict and compensate such errors to achieve a specified accuracy. While
much work has been done on the fundamentals of these problems, the thinking on said
problems has not progressed. On the hardware end, the designers of local oscillators
focus on synthesized frequency and loop noise bandwidth. This does nothing to
mitigate, or reduce frequency stability degradation in band. Similarly, there are not
systematic methods to accommodate phase and frequency anomalies such as clock
jumps. Phase locked loops are fundamentally control systems, and while control
theory has had significant advancement over the last 30 years, the design of timekeeping
sources has not advanced beyond classical control. On the software end,
single or two state oscillator models are typically embedded in a Kalman Filter to
alleviate time errors between the transmitter and receiver clock. Such models are
appropriate for short term time accuracy, but insufficient for long term time accuracy.
Additionally, flicker frequency noise may be present in oscillators, and it presents
mathematical modeling complications. This work proposes novel H∞ control methods
to address the shortcomings in the standard design of time-keeping phase locked loops.
Such methods allow the designer to address frequency stability degradation as well
as high phase/frequency dynamics. Additionally, finite-dimensional approximants of
flicker frequency noise that are more representative of the truth system than the
tradition Gauss Markov approach are derived. Last, to maintain timing accuracy in
a wide variety of operating environments, novel Banks of Adaptive Extended Kalman
Filters are used to address both stochastic and dynamic uncertainty.
ContributorsEchols, Justin A (Author) / Bliss, Daniel W (Thesis advisor) / Tsakalis, Konstantinos S (Committee member) / Berman, Spring (Committee member) / Mittelmann, Hans (Committee member) / Arizona State University (Publisher)
Created2020