Tuning optimal-robust linear MIMO controllers of chemical reactors by using Pareto optimality

Pareto optimality was introduced in order to find the better equilibrium between performance and robustness of linear controllers by the simultaneous minimization of the quadratic-error and quadratic-control functions integrals. The Pareto optimization problem was solved setting the characteristic matrix eigenvalues in the region of left complex semi plane where |Im/Re| < 1 as constraint. 2D Pareto fronts were built with the quadratic-error function integral vs. quadratic-control function integral. The proposed method was applied for tuning linear controllers of three chemical reactors with different kinetic equations and mix patterns. In the three situations, the Pareto optimality procedure improved the controllers’ performance and robustness with respect to controllers previously tuned by different methods.

► 2D Pareto fronts were applied for tuning linear controller of three chemical reactors.
► The tuning criteria were simultaneous minimization of square sum of error and control action.
► Additionally the close loop characteristic matrix eigenvalues were placed in the left complex semi-plane with Im/Re < 1.
► Results show control performance improvement with respect to controllers previously tuned, including with H2/H∞.
► Pareto fronts found the better equilibrium point between performance and robustness.