Adaptive control of cyberphysical human systems

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buir.advisorYıldız, Yıldıray
dc.contributor.authorTohidi, Seyed Shahabaldin
dc.date.accessioned2021-09-01T07:35:12Z
dc.date.available2021-09-01T07:35:12Z
dc.date.copyright2021-08
dc.date.issued2021-08
dc.date.submitted2021-08-31
dc.departmentDepartment of Mechanical Engineeringen_US
dc.descriptionCataloged from PDF version of article.en_US
dc.descriptionThesis (Ph.D.): Bilkent University, Mechanical Engineering, İhsan Doğramacı Bilkent University, 2021.en_US
dc.descriptionIncludes bibliographical references (leaves 125-139).en_US
dc.description.abstractThis dissertation focuses on the control of cyberphysical human systems in the presence of actuators’ redundancy and constraints. A novel adaptive control tech-nique is proposed to allocate control signals among redundant actuators in the presence of uncertainty and actuator saturation. The proposed method does not require any uncertainty identification or persistency of excitation assumption. The stability of the proposed method is guaranteed using Lyapunov stability analysis. In addition, a modified projection operator that can be implemented to the adaptive control allocation is proposed. This operator enables the allo-cator to handle both magnitude and rate limits of actuators. A novel sliding mode controller with time-varying sliding surface is designed to complement the adaptive allocator and guarantee stability and reference tracking in the presence of uncertainty and actuator saturation. This controller is robust to both adap-tive control allocation error and external disturbance. Furthermore, an adaptive human model is proposed to mimic the human control response in the presence of uncertainty. The proposed structure is based on the model reference adaptive control, and the adaptive laws are obtained using the Lyapunov-Krasovskii stabil-ity criteria. To validate this model, an experimental setup is employed to collect data and a statistical analysis is conducted to measure the predictive power of the pilot model. Finally, the stability limits of a human-in-the-loop closed loop control system, where the plant to be controlled has redundant actuators with uncertain dynamics, are demonstrated. Various human models with and without time delays are investigated. Simulation results are provided to demonstrate the effectiveness of the proposed methods in each chapter.en_US
dc.description.degreePh.D.en_US
dc.description.statementofresponsibilityby Seyed Shahabaldin Tohidien_US
dc.embargo.release2022-02-27
dc.format.extentxii, 167 leaves : charts ; 30 cm.en_US
dc.identifier.itemidB156883
dc.identifier.urihttp://hdl.handle.net/11693/76488
dc.language.isoEnglishen_US
dc.publisherBilkent Universityen_US
dc.rightsinfo:eu-repo/semantics/openAccessen_US
dc.subjectAdaptive controlen_US
dc.subjectCyberphysical human systemsen_US
dc.subjectControl allocationen_US
dc.subjectConstrained systemsen_US
dc.subjectHuman-in-the-loop stability analysisen_US
dc.titleAdaptive control of cyberphysical human systemsen_US
dc.title.alternativeSiber fiziksel insan sistemlerinin uyarlamalı kontrolüen_US
dc.typeThesisen_US

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