title: Solution of low-dimensional constrained model predictive control problems.
abstract: Large benefits are possible by utilizing the solution of the constrained optimization problem involved in model predictive control. For a special case of these problems, the solution can be obtained relatively easily from its relationship with the unconstrained optimum. In this paper, a visualization of the relationship between the constrained and unconstrained optimum is presented. Based upon this relationship, a method for finding the constrained optimum is proposed that is suitable for low-dimensional control systems. A comparison with a linear programming formulation on 2 x 2 and 3 x 3 problems shows that the computational effort can be 10-35 times lower. For such processes, the proposed approach may allow one to avail the benefits of optimization by using the small process control systems already present in many plants.
authors.affiliation: Department of Chemical Engineering, Dalhousie University, Halifax, NS, Canada.
authors.forename: Yash P
authors.initials: YP
authors.lastname: Gupta