A Novel Proportional−Integral-Derivative Control Configuration with Application to the Control of Batch Distillation

Abstract

The aim of this paper is to propose a novel proportional-integral-derivative (PID) control configuration based on an observer structure. Batch distillation is used as the base case study where the regulated output is the distillate composition. The proposed PID control law is derived in the framework of robust nonlinear control with modeling error compensation techniques. A reduced-order observer is proposed to estimate both the derivative of the regulated output and the underlying modeling error. These observations are subsequently used in a control loop to feedback variations of distillate composition (derivative feedback) and to counteract the effects of modeling errors. It is shown that, under certain conditions, the resulting control law is equivalent to a classical PID controller with an antireset windup scheme. Moreover, the tuning of the controller is performed very easily in terms of a prescribed closed-loop time constant and an estimation time constant. Numerical results are provided for binary and multicomponent separations. Sampled/delayed measurements and several sources of uncertainties are considered in order to provide a realistic test scenario for the proposed control design procedure.