A nonlinear model predictive control solution for a hybrid dynamic system: NASA life support system

We consider the control problem of a Variable Configuration CO2 Removal (VCCR) system, which exhibits a hybrid dynamical character due to the various configurations/modes in which one could operate the system. The VCCR is part of an overall Air Recovery-Systern of an intended human life-support system for space exploration. The objective of the control problem is to track a desired concentration profile of CO2 in a crew cabin while also ensuring safety in terms of keeping the CO2 and O-2 concentrations in the crew cabin within permissible bounds. We present a novel adaptation of the model predictive control technique for a nonlinear hybrid dynamic system. We exploit the problem structure and map the hybrid optimization problem onto a continuous nonlinear program with the aid of an appropriate representation of time and set definitions. We also discuss case studies showing the performance of this controller during off-nominal conditions.