Jobert Ludlage

A high performance model predictive controller:: application on a polyethylene gas phase reactor

Abstract This paper describes the development of a new model predictive control technology INCA ® that enables a high performance demand driven operation in the chemical process industry. The technology sustains optimal grade changes, maintains tight quality control and leads to low application development and implementation costs. An application on a polyethylene gasphase reactor is discussed.

A unified experiment design framework for detection and identification in closed-loop performance diagnosis

This paper presents a least-costly experiment design framework for closed-loop performance diagnosis using prediction error identification. The performance diagnosis methodology consists in verifying whether an identified model of the true system lies in a performance-related region of interest. The experiment design framework minimizes the overall excitation cost incurred for detecting the cause of the performance drop and re-identifying the system dynamics when the degraded performance is due to control-relevant system changes. The optimal design of excitation signals is performed for a desired detection rate and a pre-specified level of accuracy required for the re-identified model.

A Lagrangian Method for Model Reduction of Controlled Systems

This paper presents a method for closed-loop order reduction of linear systems. An approximation is carried out on the Lagrangian or Hamiltonian system that is obtained from the problem to minimize an optimization criterion subject to plant dynamics and system constraints. The resulting Hamiltonian system is reduced in complexity by means of a standard reduction techniques. The merits of the method are illustrated on an example of a distillation process.

Optimal Trajectories for Grade Change Control: Application on a Polyethylene Gas Phase Reactor

Abstract This paper describes the development of a Grade Transition optimizer PathFinder that enables a high performance demand driven operation in the chemical process industry. The technology makes use of a dynamical rigorous model based optimization of an economic criterion along a grade change trajectory. An application on a large grade slate for a polyethylene gasphase reactor is discussed.

Closed-loop performance diagnosis using prediction error identification

This paper presents a methodology to detect the origin of closed-loop performance degradation of model-based control systems. The approach exploits the statistical hypothesis testing framework. The decision rule consists of examining if an identified model of the true system lies in a set containing all models that fulfill the closed-loop performance requirements. This allows us to determine whether performance degradation arises from changes in system dynamics or from variations in disturbance characteristics. The probability of making an erroneous decision is estimated a posteriori using the known distribution of the identified model with respect to the unknown true system.

AN INDUSTRIAL APPROACH FOR EFFICIENT MODELING AND ADVANCED CONTROL OF CHEMICAL BATCH PROCESSES

Abstract Chemical batch processes offer an attractive way of producing a variety of specialty products in a highly flexible manner. However, such processes are hard to control due to the absence of the notion of a steady state operation - necessitating the use of nonlinear models- and the fact that product qualities are only measured at the end of each batch. This paper proposes a new industrial modeling and control strategy that allows significant batch time reductions to be obtained, taking physical, safety and quality constraints into account. Application to an industrial reactor shows significant improvements over classical control strategies.

Economically Optimal Grade Change Trajectories: Application on a Dow Polystyrene Process Model

Abstract A novel dynamic optimizer PathFinder has been applied to a dynamic model of a Dow polystyrene production facility at Tessenderlo, Belgium. PathFinder optimizes grade transitions subject to an economic cost function. Introduction of process constraints allows for a gradual migration from the currently used transition towards a more optimal transition. The results show a significant improvement in added value during a grade transition.

A High Performance Model Predictive Controller: Application on a Polyethylene Gas Phase Reactor

This paper describes the development of a new model predictive control technology INCA® that enables a high performance demand driven operation in the chemical process industry. The technology sustains optimal grade changes, maintains tight quality control and leads to low application development and implementation costs. An application on a polyethylene gasphase reactor is discussed.

An industrial implementation of a generic NMPC controller with application to a batch process

Abstract In the last decade a lot of attention was given to non-linear model predictive control. On one hand, in many applications linear MPC does not suffice to achieve the control goals over a wide range of operating conditions, while on the other hand many academic challenges remained in the area of NMPC, such as stability, computational complexity, etc… This paper discusses the industrial implementation of an NMPC controller at IPCOS and the different trade-offs made during the design, with the aim of clarifying the different criteria that are used in an industrial context. Results are illustrated on a chemical batch reactor.

Grade-change control using INCA model predictive controller: application on a Dow polystyrene process model

A novel model predictive control architecture INCA has been implemented on a dynamic model of a Dow polystyrene production facility at Tessenderlo, Belgium. The controller allows for a controlled grade transition and pushes the process towards more profitable operating regions during normal production, subject to prioritized requirements. Results show an excellent tracking of a desired trajectory, together with large disturbance trajectory, together with a large disturbance rejection capability during the grade transition.