Multivariable controller design for the regulation of mean arterial pressure (MAP) and cardiac output (CO) in congestive heart failure patients is restricted by the limited frequency of CO sampling. Performance criteria for the controller specify maximum allowable transient settling times for both variables, and the design should account for the inherent multirate nature of the process in order to satisfy these criteria. We present a multirate model predictive control (MPC) design for MAP and CO regulation by combined infusion of sodium nitroprusside and dopamine, based on a comprehensive nonlinear model of the system. The multirate MPC algorithm is based on nonlinear quadratic dynamic matrix control. To reduce computation time, we introduce a selective linearization technique that linearizes the model on the basis of trends in the plant-model mismatch. The problem is complicated by restrictions on initial dopamine infusion, prescribed to avoid extremely slow responses. We present a novel rule-based override (RBO) to the MPC controller that uses a set of heuristics to initialize dopamine. The performance of the MPC/RBO controller is illustrated using simulation results.
Multivariable controller design for the regulation of blood pressure and flowrate in congestive heart failure patients is typically limited by the sample time for blood flowrate. We present a multirate MPC design for the multi-drug infusion problem, based on a comprehensive nonlinear model of the system. The MPC design is based on NL-QDMC, with a selective linearization method introduced to reduce computation time. External constraints on dopamine infusion specify a 'forbidden zone' in addition to upper and lower bounds. The multirate MPC design includes a novel rule-based override that is used to avoid any infusion in this region. Simulation results are used to illustrate the performance of the controller.
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