A Hamiltonian approximation method for the reduction of controlled systems

This paper considers the problem of model reduction for controlled systems. The paper considers a dual/adjoint formulation of the general optimization problem to minimize a criterion function subject to plant dynamics and system constraints. By carrying out an approximation on the Lagrangian or Hamiltonian system that is inferred from the dual optimization problem, a reduced Hamiltonian system is obtained that approximates the optimally controlled dynamical system. The merits of the method are illustrated on an example of a controlled binary distillation process.