Design of reduced dimension explicit model predictive controller for a gas-liquid separation plant

Exact or approximate solutions to constrained linear model predictive control (MPC) problems can be precomputed offline in an explicit form as a piecewise linear state feedback defined on a polyhedral partition of the state phase. However, the complexity of the polyhedral partition often increases rapidly with the dimension of the state vector, and the number of constraints. Recently, several approaches for reducing the dimension of the explicit solution to constraint MPC problems have been developed. This paper considers the design of a reduced dimension explicit model predictive controller for a gas-liquid separation plant.