Abstract
In this article, a feedback mechanism is used for Deep Brain Stimulation of Basal Ganglia (BG) in order to control excessive tremor caused by Parkinson’s disease. Due to the nonlinearity in the Basal Ganglia model, there are some limitations in performance of previously used feedback control schemes. We enhance the linear approximation of the model by introducing an unknown input (disturbance) to the model which represents the approximation error. Then we apply an unknown input observer to estimate the system states. The estimated state is used to implement a double loop feedback with back stepping and proportional control laws simultaneously stimulating the Globus pallidus internal and Sub thalamic nucleus sections. Simulations show improvements in estimation and control.
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