Optimal design of dynamic systems under uncertainty Academic Article uri icon


  • Fundamental developments of a unified process design framework for obtaining inte-grated process and control systems design, which are economically optimal and can cope with parametric uncertainty and process disturbances, are described. Based on a dynamic mathematical model describing the process, including path constraints, interior and end-point constraints, a model that describes uncertain parameters and time-varying disturbances (for example, a probability distributions or lower/upper bounds), and a set of process design and control alternatives (together with a set of control objectives and types of controllers), the problem is posed as a mixed-integer stochastic optimal control formulation. An iterative decomposition algorithm proposed alternates between the solution of a multiperiod "design" subproblem, determining the process structure and design together with a suitable control structure (and its design characteristics) to satisfy a set of "critical" parameters/periods (for uncertainty disturbance) over time, and a time-varying feasibility analysis step, which identifies a new set of critical parameters for fixed design and control. Two examples are detailed, a mixing-tank problem to show the analytical steps of the procedure, and a ternary distillation design problem (featuring a rigorous tray-by-tray distillation model) to demonstrate the potential of the novel approach to reach solutions with significant cost savings over sequential techniques.

published proceedings


altmetric score

  • 1.25

author list (cited authors)

  • Mohideen, M. J., Perkins, J. D., & Pistikopoulos, E. N.

citation count

  • 225

complete list of authors

  • Mohideen, MJ||Perkins, JD||Pistikopoulos, EN

publication date

  • August 1996