LAUSR

A new nonlinear optimization control strategy is developed for multivariable control of an ill-conditioned, high-purity distillation column. A high-gain directional effect resulting from the ill-conditioned nature of the system causes difficulty in controllability and requires a higher performance control system. The developed optimal controller applies a minimization of energy consumption as the optimal objective function to treat the ill-conditioning effect, while wavelet neural network input/output linearizing constraints force the outputs to reach the desired set points. In this paper, ethylene dichloride purification is used as a case study. The process dynamics are evaluated based on relevant thermodynamic properties in Aspen Plus Dynamics and are controlled by the proposed controller in the MATLAB/Simulink platform. Control performances are investigated in this cosimulation environment for set point tracking and regulatory problems. The simulation results demonstrate that robust tracking is attaine...