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Iterative learning control for beam loading cancellation in electron linear accelerators Shahriari, Zahra
Abstract
Particle accelerators are mainly used as research tools for various scientific topics such as subatomic particles, astrophysical nuclear reactions, molecular and materials science. Apart from being research tools, particle accelerators can also be used for various medical purposes. The work in this thesis motivated by the control requirement for the electron linear accelerator (E-LINAC) of Advanced Rare IsotopE Laboratory (ARIEL), currently under construction in TRIUMF, Canada’s particle accelerator center. In the e-linac, electrons are accelerated up to 50 MeV along a linear beamline. Radiofrequency (RF) cavity resonators are metallic structures that accelerate charged particles along a linear axis, by providing an oscillating electric field known as the accelerating field. The particles are accelerated in bunches arriving at the cavity when the accelerating field is close to its maximum. In order to deliver a high quality beam, it is desired that all the particles receive the same amount of energy from the RF cavities. Therefore, the amplitude and phase of the accelerating field should be precisely controlled. When a bunch of particles pass through the cavity, energy is transferred from the cavity to the beam. As a result of the interaction between the cavity field and the beam, the accelerating field decreases. This phenomenon is called the beam loading effect. The control goal is to cancel the beam loading effect so that it does not affect the acceleration of the following particles. The feedback controller in the loop is not fast enough to meet the control requirements. Therefore, a feedforward controller is needed for fast response. In this thesis, an Iterative learning control (ILC) system is developed to cancel the beam loading effect. Two implementations of ILC are presented, filter-based ILC and norm-optimal ILC. The transient response of filter-based ILC is analyzed using pseudospectra, the eigenvalues of the perturbed transfer matrix. The norm-optimal ILC is designed as a finite-state machine (FSM) to be implemented on field-programmable gate array (FPGA) hardware. The filter-based ILC is tested on the cavities in TRIUMF e-linac, and the test results show successful cancellation of the beam loading effect, meeting the control requirements.
Item Metadata
Title |
Iterative learning control for beam loading cancellation in electron linear accelerators
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Creator | |
Supervisor | |
Publisher |
University of British Columbia
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Date Issued |
2021
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Description |
Particle accelerators are mainly used as research tools for various scientific topics such as subatomic particles, astrophysical nuclear reactions, molecular and materials science. Apart from being research tools, particle accelerators can also be used for various medical purposes. The work in this thesis motivated by the control requirement for the electron linear accelerator (E-LINAC) of Advanced Rare IsotopE Laboratory (ARIEL), currently under construction in TRIUMF, Canada’s particle accelerator center. In the e-linac, electrons are accelerated up to 50 MeV along a linear beamline. Radiofrequency (RF) cavity resonators are metallic structures that accelerate charged
particles along a linear axis, by providing an oscillating electric field known as the accelerating field. The particles are accelerated in bunches arriving at the cavity when the accelerating field is close to its maximum. In order to deliver a high quality beam, it is desired that all the particles receive the same amount of energy from the RF cavities. Therefore, the amplitude and phase of the accelerating field should be precisely controlled. When a bunch of particles pass through the cavity, energy is transferred from the cavity to the beam. As a result of the interaction between the cavity field and
the beam, the accelerating field decreases. This phenomenon is called the beam loading effect. The control goal is to cancel the beam loading effect so that it does not affect the acceleration of the following particles. The feedback controller in the loop is not fast enough to meet the control requirements. Therefore, a feedforward controller is needed for fast response. In this thesis, an Iterative learning control (ILC) system is developed to cancel the beam loading effect. Two implementations of ILC are presented, filter-based ILC and norm-optimal ILC. The transient response of filter-based ILC is analyzed using pseudospectra, the eigenvalues of the perturbed transfer matrix. The norm-optimal ILC is designed as a finite-state machine (FSM) to be implemented on field-programmable gate array (FPGA) hardware. The filter-based ILC is tested on the cavities in TRIUMF e-linac, and the test results show successful cancellation of the beam loading effect, meeting the control requirements.
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Genre | |
Type | |
Language |
eng
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Date Available |
2021-08-11
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Provider |
Vancouver : University of British Columbia Library
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Rights |
Attribution-NonCommercial-NoDerivatives 4.0 International
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DOI |
10.14288/1.0401371
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URI | |
Degree | |
Program | |
Affiliation | |
Degree Grantor |
University of British Columbia
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Graduation Date |
2021-11
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Campus | |
Scholarly Level |
Graduate
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Rights URI | |
Aggregated Source Repository |
DSpace
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Rights
Attribution-NonCommercial-NoDerivatives 4.0 International