Evaluation of inferential and parallel cascade schemes for distillation control

Abstract

This paper presents a comparative assessment of inferential and parallel cascade schemes for controlling the top-product composition of a simulated multicomponent distillation tower. The steady-state data employed in the simulation study pertain to an Industrial type column. The paper compares the closed-loop response of the single-temperature feedback scheme with the inferential and parallel cascade schemes. The findings of this work support the implementation of the inferential control scheme for this column.

An adaptive estimation algorithm for inferential control

“…In fact, the evaluation work carried out by Patke et al (1982) indicated that an inferential control scheme based on the output estimation technique proposed by Brosilow and co-workers can result in significant offsets. If G1(z-l), Gz-(z-l), H1(z-l), and H2(z-') were all known, u ( t ) and u ( t ) could be used in eq 6 or 7 to compute at steady state.…”

“…If G1(z-l), Gz-(z-l), H1(z-l), and H2(z-') were all known, u ( t ) and u ( t ) could be used in eq 6 or 7 to compute at steady state. Although no offset problems arise with this control configuration, the transient performance can at times be poor (Patke et al, 1982). Methods for minimizing the steady-state estimation error by appropriate choice of the secondary measurements were also proposed.…”

“…Examples of industrial situations where this can occur are in product composition control of distillation columns (Patke et al, 1982) and chemical reactors (Wright et al, 1977). This results in large deviations from the desired output and consequently long disturbance recovery times.…”

State estimation and inferential control for a reactive batch distillation column

“…Thus, in the presence of unmeasured disturbances, inferential control is one of the solutions that can be used to control an unmeasured process output. Although, in distillation columns, the compositions are strong functions of temperatures (Kano et al, 2000), in multi-component distillation, temperature control is not always effective for composition control, since the tray temperature does not correspond exactly to the product compositions (Patke et al, 1982, Kano et al, 2000. Therefore, it is important to be able to infer compositions from secondary measurements like temperatures, flows, pressures, etc.…”

Implementation and performance evaluation of composition controllers for distillation columns

“…( 1 ) A comprehensive assessment of inferential and parallel cascade schemes for controlling the top-product composition of a simulated multicomponent distillation column ( 2 ) suggested inferential control scheme for certain distillation columns is superior to the parallel cascade and traditional control schemes.…”