Robust Multivariable Control of Ill-Conditioned Plants – A Case Study for High-Purity Distillation

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 attained, while compensation of the input disturbances is effectively improved compared with a model predictive controller.

Section: Introductionmentioning

confidence: 99%

Optimization-Based Control Strategy with Wavelet Network Input–Output Linearizing Constraint for an Ill-Conditioned High-Purity Distillation Column

Tanakunmas

Panjapornpon

Tawai

et al. 2017

“…Dynamic and steady-state indicators are used in different articles. Some authors have used steady-state indices; − others have preferred frequency-dependent indices − …”

Section: Introductionmentioning

confidence: 99%

Applicability of Desirability Function for Control Structure Design in the Frequency Domain

Haragovics

Kencse

Mizsey

2012

In this work, the application of desirability function on controllability indices in the frequency domain is studied and a methodology is presented for its proper application. To design control structures, controllability indices are often used. Different indices represent different controllability attributes of the investigated system or systems; thus, their results might not be in agreement. With the desirability function, it is possible, however, to aggregate the different indices and a final ranking can be obtained, which may substitute time domain studies. Two different fields are examined: control structure variable pairing and selecting a distillation scheme that shows the best controllability features. On one hand, for the variable pairing step of the control structure design, the methodology does not deliver acceptable results, because controllability indices prove to be inaccurate in such cases on which the calculation is based. On the other hand, the methodology delivers similar result for the selection of the right distillation scheme from the controllability point of view to that of the load rejection investigations. This result shows the right area for the applicability of the methodology based on the desirability function.

“…Semino et al designed a double-filter internal model control (IMC) controller for ill-conditioned distillation columns. Razzaghi and Shahraki , showed that acceptable closed-loop performance could be achieved for an ill-conditioned high-purity distillation column by use of the structured singular value. The benefit of this method is its reliance on a simple filter structure depending on fewer parameters.…”

Section: Introductionmentioning

confidence: 99%

“…Since the order of the ODOF controller is usually high, TDOF controllers are designed for the CDC benchmark problem in refs − . Yaniv et al proposed a quantitative feedback theory (QFT) approach for the ill-conditioned plant.…”

Section: Introductionmentioning

confidence: 99%

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Two-Degree-of-Freedom Controller Design for an Ill-Conditioned Process Using H₂ Decoupling Control

Zhang

Chen³

et al. 2012

In this paper, a two-degree-of-freedom (TDOF) controller is designed for an ill-conditioned process based on the H 2 decoupling control method. The ill-conditioned process considered stems from the benchmark problem formulated in the IEEE Conference on Decision and Control (CDC). The goal of this paper is to show that lower order controllers can be reached with respect to the given plant and the corresponding design specifications. The orders of the designed TDOF controllers are 2 and 1, respectively, which is much lower than the previously developed methods. The additional benefit is that the new design procedure is simpler than the developed methods as well. In the proposed design procedure, no weight function needs to be chosen and the controller is given in an analytical form. Simulation shows that the designed controllers satisfy all design specifications of the CDC problem.