The operation of chemical processes often requires respecting constraints on manipulated inputs and process states. Input constraints typically reflect limits on the capacity of control actuators, such as valves or pumps, whereas state constraints represent desirable ranges of operation for process variables, such as temperatures or concentrations. Constraints, however, limit the set of initial...

The language-based theory of regions, stemming from the area of Petri net synthesis, forms a fundamental basis for Integer Linear Programming (ILP)-based process discovery. Based on example behavior in an event log, a process model is derived that aims to describe the observed behavior. Building on top of the existing ILP-formulation, we present a new ILP-based process discovery formulation tha...

Multi-stage compression is the normal method to achieve pipeline pressures of 100 bara for the transport of carbon dioxide (CO2) after capture in a carbon capture and storage (CCS) scheme. An alternative method is to partially compress the gas, liquefy it and then pump the liquid CO2 to the required pressure. The advantage of this process is that the CO2 stream can be further purified through l...

The hierarchical Dirichlet process (HDP) can provide a nonparametric prior for a mixture model with grouped data, where mixture components are shared across groups. However, the computational cost is generally very high in terms of both time and space complexity. Therefore, developing a method for fast inference of HDP remains a challenge. In this paper, we assume a symmetric multiprocessing (S...

In previous work, action languages have predominantly been concerned with domains in which values are static unless changed by an action. Real domains, however, often contain values that are in constant change. In this paper we introduce an action language for modeling such hybrid domains called the process description language. We discuss the syntax and semantics of the language, model an exam...

Abstract: In this paper hybrid fuzzy model based predictive control (HFMBPC) is addressed, proposed and tested. The proposed hybrid fuzzy convolution model consists of a steady-state fuzzy model and a gain independent impulse response model. The proposed model is tested in model based predictive control of the concentration control in the chemical reactor, manipulating its flow rate. The paper ...

The work that is presented here was initiated by question of a colleague from the mechanical engineering department. He was analysing several industrial manufacturing processes (a tire production line, a cookie baking line, etc.). These processes were modeled in a procedural kind of programming language (called “χ” [AvdMR94]) extended with hybrid features such as continuous variables defined by...

Observers or state estimators are devices applied to approximate unknown parameters that are due to uncertain parameters, noise, disturbances and mismatch. It is important to identify those variables prior to construct a control system and avoid fault or process disruption. In certain chemical processes, such observer usage produced unsatisfactory results therefore hybrid approached is the best...

This paper deals with simulation modeling of software processes and proposes the combination of three traditional modeling methods (analytical, continuous and discrete-event) into a unique hybrid two-level modeling approach. At the higher abstraction level, the process is modeled by a discreteevent queuing network, which represents the component activities (i.e. service stations), their interac...

In the area of business process modelling, declarative notations have been proposed as alternatives to notations that follow the dominant, imperative paradigm. Yet, the choice between an imperative or declarative style of modelling is not always easy to make. Instead, a mixture of these styles is sometimes preferable. This observation has underpinned recent calls for so-called hybrid process mo...