Korrapati, Sujana2017-07-182017-07-182017-03https://hdl.handle.net/11299/188785University of Minnesota M.S.E.E. thesis. March 2017. Major: Electrical Engineering. Advisor: Jiann Shiou Yang. 1 computer file (PDF); iv, 55 pages.A study of using an adaptive inverse dynamics control technique to a two-compartment modeled respiratory system. Based on the nonlinear respiratory model and desired respiratory volumes, the adaptive inverse dynamics control scheme consisting of a control law and an adaptation law is then applied. The control law has the structure of the two-compartment inverse dynamical model but uses estimates of the dynamics parameters in the computation of pressure applied to the lungs. The adaptation law uses the tracking error to compute the parameter estimates for the control law. The preliminary results indicate that the tracking errors can be improved if the parameter values associated with the adaptation law are properly chosen, and the performance is also robust despite relatively large deviations in the initial estimates of the system parametersenThesis or Dissertation