Design of a rule-based control system for decentralized adaptive control of robotic manipulators

Persistent Link:
http://hdl.handle.net/10150/276874
Title:
Design of a rule-based control system for decentralized adaptive control of robotic manipulators
Author:
Karakaşoğlu, Ahmet, 1961-
Issue Date:
1988
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:
This thesis is concerned with the applicability of model reference adaptive control to the control of robot manipulators under a wide range of configuration and payload changes, and a comparison of the performance of this technique with that of the non-adaptive schemes. The dynamic equations of robot manipulators are highly nonlinear and are difficult to determine precisely. For these reasons there is an interest in applying adaptive control techniques to robot manipulators. In this work, the detailed performance of three adaptive controllers are studied and compared with that of a non-adaptive controller, namely, the computed torque control scheme. Computer simulation results show that the use of adaptive control improves the performance of the manipulator despite changes in the payload or in the manipulator configuration. Making use of these results, a rule-based controller is developed by dividing a given manipulation task into portions where a particular adaptive control scheme, based on a specific linearized subsystem model, performs best. This strategy of selecting the proper controller during each portion of the overall task yields a performance having the least deviation from the desired trajectory during the entire length of the task.
Type:
text; Thesis-Reproduction (electronic)
Keywords:
Robots -- Control systems.; Adaptive control systems.; Intelligent control systems.; Expert systems (Computer science); Manipulators (Mechanism)
Degree Name:
M.S.
Degree Level:
masters
Degree Program:
Graduate College; Electrical and Computer Engineering
Degree Grantor:
University of Arizona

Full metadata record

DC FieldValue Language
dc.language.isoen_USen_US
dc.titleDesign of a rule-based control system for decentralized adaptive control of robotic manipulatorsen_US
dc.creatorKarakaşoğlu, Ahmet, 1961-en_US
dc.contributor.authorKarakaşoğlu, Ahmet, 1961-en_US
dc.date.issued1988en_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.abstractThis thesis is concerned with the applicability of model reference adaptive control to the control of robot manipulators under a wide range of configuration and payload changes, and a comparison of the performance of this technique with that of the non-adaptive schemes. The dynamic equations of robot manipulators are highly nonlinear and are difficult to determine precisely. For these reasons there is an interest in applying adaptive control techniques to robot manipulators. In this work, the detailed performance of three adaptive controllers are studied and compared with that of a non-adaptive controller, namely, the computed torque control scheme. Computer simulation results show that the use of adaptive control improves the performance of the manipulator despite changes in the payload or in the manipulator configuration. Making use of these results, a rule-based controller is developed by dividing a given manipulation task into portions where a particular adaptive control scheme, based on a specific linearized subsystem model, performs best. This strategy of selecting the proper controller during each portion of the overall task yields a performance having the least deviation from the desired trajectory during the entire length of the task.en_US
dc.typetexten_US
dc.typeThesis-Reproduction (electronic)en_US
dc.subjectRobots -- Control systems.en_US
dc.subjectAdaptive control systems.en_US
dc.subjectIntelligent control systems.en_US
dc.subjectExpert systems (Computer science)en_US
dc.subjectManipulators (Mechanism)en_US
thesis.degree.nameM.S.en_US
thesis.degree.levelmastersen_US
thesis.degree.disciplineGraduate Collegeen_US
thesis.degree.disciplineElectrical and Computer Engineeringen_US
thesis.degree.grantorUniversity of Arizonaen_US
dc.identifier.proquest1335693en_US
dc.identifier.oclc22499580en_US
dc.identifier.bibrecord.b17444469en_US
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