Comparison of self-tuning and predictive control algorithms applied to a nonlinear process

High-purity distillation columns present gain, time constants, and delays that vary nonlinearly, making the application of conventional controllers difficult. The behavior of linear and nonlinear self-tuning and predictive algorithms for single-input, single-output (SISO) cases applied to this class of processes is analyzed. Simulation results show that all the controllers can deal efficiently with this type of process with respect to load rejection and set-point tracking, with the predictive algorithm exhibiting the best performance