Genichi Emoto

Performance evaluation of two industrial MPC controllers

This paper presents case studies of the performance evaluation of two industrial multivariate model predictive control (MPC) based controllers at the Mitsubishi chemical complex in Mizushima, Japan: (1) a 6-output, 6-input para-xylene (PX) production process with six measured disturbance variables that are used for feedforward control; and (2) a multivariate MPC controller for a 6-output, 5-input poly-propylene splitter column with two measured disturbances. A generalized predictive controller-based MPC algorithm has been implemented on the PX process. Data from the PX unit before and after the MPC implementation are analyzed to obtain and compare several different measures of multivariate controller performance. The second case study is concerned with performance assessment of a commercial MPC controller on a propylene splitter. A discussion on the diagnosis of poor performance for the second MPC application suggests significant model-plant-mismatch under varying load conditions and highlights the role of constraints.

Closed loop identification and control loop reconfiguration: an industrial case study

Abstract The results of a joint university–industry collaborative project for control loop reconfiguration using closed loop experimental data from a fuel gas pressure control system are described in this paper. The fuel gas pressure was being regulated using a butane stream. For economic reasons, it was necessary to switch control to the ethane stream. Previous attempts at effecting this changeover had proved unsuccessful. In this study, a powerful system identification technique namely Canonical Variate Analysis (CVA) was employed to obtain the empirical plant models. A PI controller was then designed using the direct synthesis method. Acceptable closed loop behavior was obtained with little online tuning.

Modeling and Identification for Quench Column Bottom Temperature Control

Abstract Simplified process models such as first-order plus time-delay models are often used for -based controller tuning. This paper shows that such a simplified assumption is not always appropriate through a case study of an ethylene plant quench column bottom temperature control loop. It is important to understand the physical meaning of the process behavior in modeling of complicated processes. This practical experience shows that when a high-order model was decomposed to several low order models based on physical meaning and appropriate simplification of the high-order model, a better control result was obtained. Further, this physically explained transfer function model could be used to estimate a reasonable model uncertainty.

Industrial applications of system identification and control of processes with recycles

Abstract Process systems with material and/or energy recycles are ubiquitous in the chemical industry. In this paper we address the following problem: Given a manipulated variable and a controlled variable for a process unit which is part of a larger integrated system, how does one proceed with system identification, control structure selection and controller design? While empirical modelling and control design can be easier for stand-alone process units, it can be a very challenging task for units with recycle. The purpose of this paper is to highlight the issues, concepts and challenges using several industrial case studies.

Ethylene quench column optimal operation and controllability analysis

Abstract The operating conditions for a heat-integrated ethylene quench column are optimized and diagnosed for controllability and resiliency. Since a bank of seawater coolers largely meets the columns cooling duty requirements, the heat-exchanger by-pass flow fractions were optimized as a function of seawater temperature, using a specially adapted genetic algorithm. The controllability and resiliency of the quench column are studied and two alternative MIMO control configurations are investigated. Of particular interest was the impact of the nominal operating position of the bypass on disturbance rejection capacity. It was found that the resiliency of the column could be significantly enhanced by repositioning the nominal operating point of the main bypass valve and at the same time, the overall heat recovery in the seawater coolers could be enhanced, leading to significant savings in operating costs.

Modeling and Control System Design of a Crystallizer Train for Para-xylene Production

Abstract Abstract A dynamic process model of an industrial crystallizer train for para-xylene production, which consists of five scraped surface crystallizers, two hydrocyclone separators, and two centrifugal separators, is developed for control system design. The model is identified by using real plant data. Optimal operating policies, which consider feed maximization and load distribution among the crystallizers, are derived, and multiloop controller is configured to realize the operating policy.

Ethylene Quench Column Optimal Operation and Controllability Analysis

Abstract The operating conditions for a heat-integrated ethylene quench column are optimized and diagnosed for controllability and resiliency. Since a bank of seawater coolers largely meets the column’s cooling duty requirements, the heat-exchanger by-pass flow fractions were optimized as a function of seawater temperature, using a specially adapted genetic algorithm. The controllability and resiliency of the quench column are studied and two alternative MIMO control configurations are investigated. Of particular interest was the impact of the nominal operating position of the bypass on disturbance rejection capacity.