Controls and Control Theory Commons^™

Evaluating Eeg–Emg Fusion-Based Classification As A Method For Improving Control Of Wearable Robotic Devices For Upper-Limb Rehabilitation, Jacob G. Tryon

Electronic Thesis and Dissertation Repository

Musculoskeletal disorders are the biggest cause of disability worldwide, and wearable mechatronic rehabilitation devices have been proposed for treatment. However, before widespread adoption, improvements in user control and system adaptability are required. User intention should be detected intuitively, and user-induced changes in system dynamics should be unobtrusively identified and corrected. Developments often focus on model-dependent nonlinear control theory, which is challenging to implement for wearable devices.

One alternative is to incorporate bioelectrical signal-based machine learning into the system, allowing for simpler controller designs to be augmented by supplemental brain (electroencephalography/EEG) and muscle (electromyography/EMG) information. To extract user intention better, sensor …

Nonlinear Adaptive Control Of Drilling Processes, Maksim Faronov

Electronic Thesis and Dissertation Repository

This work deals with the modeling and control of automated drilling operations. Advances in drilling automation are of substantial importance because improvements in drilling control algorithms will result in more efficient drilling, which is beneficial from both economic and environmental points of view. While the primary application of the results is extraction of natural resources, potentially there exists a wide range of applications, including offshore exploration, archaeological research, and automated extraterrestrial mining, where implementation of new methods and control algorithms for drilling processes can bring substantial benefits.

The main contribution of the thesis is development of new methods and algorithms …

Exploration Of Force In Movement And Perception In Parkinson’S Disease, Caroline Stefanie Aitken

Electronic Thesis and Dissertation Repository

Parkinson’s Disease (PD) causes force control deficits in upper and lower limbs. About 50% of patients with advanced PD develop freezing of gait (FOG). There is limited research comparing force control in PD with and without FOG, especially in upper limbs. It has been suggested that motor control deficits in PD are related to deficits in kinesthesia, but there is conflicting evidence whether levodopa alleviates kinesthetic deficits. In this thesis, force control was explored using an upper-and-lower-limb haptics-enabled robot in a reaching task, and kinesthesia was investigated using a haptic device in a force discrimination task while participants were on …