Synchronization and System Identification Using Symbolic Dynamics

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dc.contributor.advisorLeung, Henry
dc.contributor.authorMukhopadhyay, Sumona
dc.contributor.committeememberFar, Behrouz
dc.contributor.committeememberThomas, Gabriel
dc.contributor.committeememberYanushkevich, Svetlana
dc.contributor.committeememberXue, Deyi
dc.date2018-06
dc.date.accessioned2018-01-25T18:33:35Z
dc.date.available2018-01-25T18:33:35Z
dc.date.issued2018-01-22
dc.description.abstractResearch on communication, signal processing and robotics have benefited from chaos theory. In robotics, chaos is applied in path planning and coverage, which can be improved by employing multiple robots working concurrently. However, collaborating multiple chaotic robots is difficult since chaos synchronization is difficult to realize in the presence of noise. In signal processing, chaos is applied in system identification problem. But existing chaos-based identification techniques impose limitations caused by not exploiting characteristics unique to the input information. The first problem considered in this thesis is collaborative exploration among autonomous mobile robots using chaos. To achieve this, the chaotic mobile robots are synchronized by chaos synchronization that can control multiple robots. However, the critical issue of noise introduces instabilities in motion thereby hindering collaboration. This work proposes a novel technique which uses symbols to achieve collaboration between chaotic robots in presence of noise. The second problem considered is system identification without any knowledge of input, known as blind identification. Performance of existing blind identification methods degrades at strong noise. This problem is addressed in this work by using a chaos representation of the random symbolic input. The blind identification approach using chaos in this work is analytically proved to achieve the optimal performance bound of non-blind using non-chaotic input. Results show superior performance in comparison to existing methods. The third problem considered is blind system identification when the input is a chaotic signal. An estimator for a chaotic property is derived which is used as the optimization criteria for identification. Results show the merit of chaos-based system identification over popular techniques. The outcome of the work presented in this thesis is shown to work well when applied to symbolic signal processing using chaos and can be used for harnessing noise for useful engineering purposes such as multi-robot collaborative exploration using autonomous chaotic robots.en_US
dc.identifier.citationMukhopadhyay, S. (2018). Synchronization and System Identification Using Symbolic Dynamics (Doctoral thesis, University of Calgary, Calgary, Canada). Retrieved from https://prism.ucalgary.ca.en_US
dc.identifier.doihttp://dx.doi.org/10.11575/PRISM/5399
dc.identifier.urihttp://hdl.handle.net/1880/106318
dc.language.isoenen_US
dc.publisher.facultySchulich School of Engineeringen_US
dc.publisher.institutionUniversity of Calgaryen
dc.rightsUniversity of Calgary graduate students retain copyright ownership and moral rights for their thesis. You may use this material in any way that is permitted by the Copyright Act or through licensing that has been assigned to the document. For uses that are not allowable under copyright legislation or licensing, you are required to seek permission.en_US
dc.subjectsymbolic dynamicsen_US
dc.subjectsystem identificationen_US
dc.subjectchaosen_US
dc.subjectchaotic systemen_US
dc.subjectchaotic signalen_US
dc.subjectcommunicationen_US
dc.subjectparameter estimationen_US
dc.subject.classificationComputer Scienceen_US
dc.subject.classificationEngineeringen_US
dc.subject.classificationEngineering--Electronics and Electricalen_US
dc.subject.classificationRoboticsen_US
dc.titleSynchronization and System Identification Using Symbolic Dynamicsen_US
dc.typedoctoral thesisen_US
thesis.degree.disciplineEngineering – Electrical & Computeren_US
thesis.degree.grantorUniversity of Calgaryen_US
thesis.degree.nameDoctor of Philosophy (PhD)en_US
ucalgary.item.requestcopytrue
ucalgary.thesis.checklistI confirm that I have submitted all of the required forms to Faculty of Graduate Studies.en_US
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