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dc.contributor.authorNguyen, Chuong Hoangen_US
dc.date.accessioned2016-06-04T08:00:48Z
dc.date.available2016-06-04T08:00:48Z
dc.date.issued2016-06-03en_US
dc.identifier.othervt_gsexam:7829en_US
dc.identifier.urihttp://hdl.handle.net/10919/71312
dc.description.abstractFunctional Electrical Stimulation (FES) is a technique that applies electrical currents to nervous tissue in order to actively induce muscle contraction. Recent research has shown that FES provides a promising treatment to restore functional tasks due to paralysis caused by spinal cord injury, head injury, and stroke, to mention a few. Therefore, the overarching goal of this research work is to develop FES controllers to enable patients with movement-disorder to control their limbs in a desired manner and, in particular, to aid Parkinson's patients to suppress hand tremor. In our effort to develop strategies for muscle stimulation control, we first implement a model-based control technique assuming that all the states are measurable. The Hill-type muscle model coupled with a simplified 2DoF model of the arm is used to study the performance of our proposed adaptive sliding mode controller for simulation purpose. However, in the more practical situations, human limb dynamics are extremely complicate and it is inadequate to use model based controllers, especially considering there are still technical limitations that allow in vivo measurements of muscle activity. To tackle these challenges, we have developed output feedback adaptive control approaches for a class of unknown multi-input multi-output systems. Such control strategies are first developed for linear systems, and then extended to the nonlinear case. The proposed controllers, supported by experimental results, require minimum knowledge of the system dynamics and avoid many restrictive assumptions typically found in the literature. Therefore, we expect that the results introduced in this dissertation can provide a solution for a wide class of nonlinear uncertain systems, with focus on practical issues such as partial state measurement and the presence of mismatched uncertainties.en_US
dc.format.mediumETDen_US
dc.publisherVirginia Techen_US
dc.rightsThis Item is protected by copyright and/or related rights. Some uses of this Item may be deemed fair and permitted by law even without permission from the rights holder(s), or the rights holder(s) may have licensed the work for use under certain conditions. For other uses you need to obtain permission from the rights holder(s).en_US
dc.subjectUnknown system dynamicsen_US
dc.subjectnon-model based controlen_US
dc.subjectmodel predictoren_US
dc.subjectnonlinear MIMO systemsen_US
dc.subjectoutput feedback controlen_US
dc.subjectadaptive control.en_US
dc.titleAdaptive Predictor-Based Output Feedback Control of Unknown Multi-Input Multi-Output Systems: Theory and Application to Biomedical Inspired Problemsen_US
dc.typeDissertationen_US
dc.contributor.departmentMechanical Engineeringen_US
dc.description.degreePh. D.en_US
thesis.degree.namePh. D.en_US
thesis.degree.leveldoctoralen_US
thesis.degree.grantorVirginia Polytechnic Institute and State Universityen_US
thesis.degree.disciplineMechanical Engineeringen_US
dc.contributor.committeechairLeonessa, Alexanderen_US
dc.contributor.committeememberWicks, Alfred L.en_US
dc.contributor.committeememberSouthward, Steve C.en_US
dc.contributor.committeememberKurdila, Andrew J.en_US
dc.contributor.committeememberAbaid, Nicoleen_US


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