Persistent Link:
http://hdl.handle.net/10150/185999
Title:
Application of control theory to the hyperthermia problem.
Author:
Potocki, Jon Kyle.
Issue Date:
1992
Publisher:
The University of Arizona.
Rights:
Copyright © is held by the author. Digital access to this material is made possible by the University Libraries, University of Arizona. Further transmission, reproduction or presentation (such as public display or performance) of protected items is prohibited except with permission of the author.
Abstract:
The objective of a hyperthermia cancer treatment is to heat the tumor tissue to a therapeutic level while limiting the detrimental effects experienced by the surrounding normal tissue. To achieve an optimal treatment requires knowledge of the resulting temperature response and an understanding of the complex interaction between the thermal response, the applied power, and the blood flow in the target tissue region. This dissertation considers model reduction to overcome the large dimensions associated with thermal modelling, extended Kalman filtering to estimate both the unmeasured temperature states and the unknown blood perfusion magnitudes, optimization of the applied power to achieve the best thermal response, and optimal servomechanism control to attain the desired regulated output tracking. A controller methodology that combines thermal estimation, applied power optimization, and optimal servomechanism control with a simple expert system shell is examined. This controller methodology is analyzed for a simulated scanned focussed ultrasound system (SFUS) based upon the bioheat transfer equation (BHTE) model of the thermal response in the target region. The results of the presented studies illustrate the following important points. First, open-loop reduced-order models based on the balanced transformation provide drastic model reduction for controller design purposes. Second, the success of thermal estimation depends on the number and the location of the thermal sensors, and the accuracy of the modelled blood perfusion profile. Third, multiple modelling in estimation provides an alternate technique for overcoming model mismatch associated with the modelling of the blood perfusion pattern. Fourth, the choice of the set points for the optimal servomechanism controller play a crucial role in the resulting tissue temperatures. Fifth, the scan parameter sets that result in optimal SFUS power profiles need to be changed on-line during a treatment as the blood perfusion magnitude and pattern are estimated. Finally, to fully automate a hyperthermia treatment requires that the expertise of the clinician be incorporated into the controller design. Hierarchical control provides a means of incorporating the expert system shell at the higher levels of the controller, while maintaining optimal servomechanism control at the lower levels.
Type:
text; Dissertation-Reproduction (electronic)
Keywords:
Dissertations, Academic.; System theory.; Electrical engineering.; Control theory.
Degree Name:
Ph.D.
Degree Level:
doctoral
Degree Program:
Electrical and Computer Engineering; Graduate College
Degree Grantor:
University of Arizona
Committee Chair:
Tharp, H.S.

Full metadata record

DC FieldValue Language
dc.language.isoenen_US
dc.titleApplication of control theory to the hyperthermia problem.en_US
dc.creatorPotocki, Jon Kyle.en_US
dc.contributor.authorPotocki, Jon Kyle.en_US
dc.date.issued1992en_US
dc.publisherThe University of Arizona.en_US
dc.rightsCopyright © is held by the author. Digital access to this material is made possible by the University Libraries, University of Arizona. Further transmission, reproduction or presentation (such as public display or performance) of protected items is prohibited except with permission of the author.en_US
dc.description.abstractThe objective of a hyperthermia cancer treatment is to heat the tumor tissue to a therapeutic level while limiting the detrimental effects experienced by the surrounding normal tissue. To achieve an optimal treatment requires knowledge of the resulting temperature response and an understanding of the complex interaction between the thermal response, the applied power, and the blood flow in the target tissue region. This dissertation considers model reduction to overcome the large dimensions associated with thermal modelling, extended Kalman filtering to estimate both the unmeasured temperature states and the unknown blood perfusion magnitudes, optimization of the applied power to achieve the best thermal response, and optimal servomechanism control to attain the desired regulated output tracking. A controller methodology that combines thermal estimation, applied power optimization, and optimal servomechanism control with a simple expert system shell is examined. This controller methodology is analyzed for a simulated scanned focussed ultrasound system (SFUS) based upon the bioheat transfer equation (BHTE) model of the thermal response in the target region. The results of the presented studies illustrate the following important points. First, open-loop reduced-order models based on the balanced transformation provide drastic model reduction for controller design purposes. Second, the success of thermal estimation depends on the number and the location of the thermal sensors, and the accuracy of the modelled blood perfusion profile. Third, multiple modelling in estimation provides an alternate technique for overcoming model mismatch associated with the modelling of the blood perfusion pattern. Fourth, the choice of the set points for the optimal servomechanism controller play a crucial role in the resulting tissue temperatures. Fifth, the scan parameter sets that result in optimal SFUS power profiles need to be changed on-line during a treatment as the blood perfusion magnitude and pattern are estimated. Finally, to fully automate a hyperthermia treatment requires that the expertise of the clinician be incorporated into the controller design. Hierarchical control provides a means of incorporating the expert system shell at the higher levels of the controller, while maintaining optimal servomechanism control at the lower levels.en_US
dc.typetexten_US
dc.typeDissertation-Reproduction (electronic)en_US
dc.subjectDissertations, Academic.en_US
dc.subjectSystem theory.en_US
dc.subjectElectrical engineering.en_US
dc.subjectControl theory.en_US
thesis.degree.namePh.D.en_US
thesis.degree.leveldoctoralen_US
thesis.degree.disciplineElectrical and Computer Engineeringen_US
thesis.degree.disciplineGraduate Collegeen_US
thesis.degree.grantorUniversity of Arizonaen_US
dc.contributor.chairTharp, H.S.en_US
dc.contributor.committeememberRoemer, R.B.en_US
dc.contributor.committeememberSundareshan, M.K.en_US
dc.identifier.proquest9307663en_US
dc.identifier.oclc713876569en_US
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