Model predictive control techniques for hybrid systems

Evolving fuzzy and neuro-fuzzy approaches in clustering, regression, identification, and classification: A Survey

Long-term effect of dissolved oxygen on partial nitrification performance and microbial community structure.

Mathematics and Computers in Simulation

Background and Purpose: The aim of this paper is to present the influence of Industry 4.0 on the development of the new simulation modelling paradigm, embodied by the Digital Twin concept, and examine the adoption of the new paradigm via a multiple case study involving real-life R/D cases involving academia and industry. 
Design: We introduce the Industry 4.0 paradigm, presents its background, current state of development and its influence on the development of the simulation modelling paradigm. Further, we present the multiple case study methodology and examine several research and development projects involving automated industrial process modelling, presented in recent scientific publications and conclude with lessons learned. 
Results: We present the research problems and main results from five individual cases of adoption of the new simulation modelling paradigm. Main lesson learned is that while the new simulation modelling paradigm is being adopted by big companies and SMEs, there are significant differences depending on company size in problems that they face, and the methodologies and technologies they use to overcome the issues.
Conclusion: While the examined cases indicate the acceptance of the new simulation modelling paradigm in the industrial and scientific communities, its adoption in academic environment requires close cooperation with industry partners and diversification of knowledge of researchers in order to build integrated, multi-level models of cyber-physical systems. As shown by the presented cases, lack of tools is not a problem, as the current generation of general purpose simulation modelling tools offers adequate integration options.

/pdf/industry-4-0-and-the-new-simulation-modelling-paradigm-227jrixl4t.pdf

Industry 4.0 and the New Simulation Modelling Paradigm

http://msc.fe.uni-lj.si/Papers/CCE2007_Karer.pdf

Hybrid fuzzy model-based predictive control of temperature in a batch reactor

http://msc.fe.uni-lj.si/Papers/MCS_Music2011.pdf

Original Articles: Coloured Petri net scheduling models: Timed state space exploration shortages

The paper presents the design of an algorithm used in control of a sequencing batch reactor (SBR) for wastewater treatment. The algorithm is used for the on-line optimization of the batch phases duration which should be applied due to the variable input wastewater. Compared to an operation with fixed times of batch phases, this kind of a control strategy improves the treatment quality and reduces energy consumption. The designed control algorithm is based on following the course of some simple indirect process variables (i.e. redox potential, dissolved oxygen concentration and pH), and automatic recognition of the characteristic patterns in their time profile. The algorithm acts on filtered on-line signals and is based on heuristic rules. The control strategy was developed and tested on a laboratory pilot plant. To facilitate the experimentation, the pilot plant was superimposed by a computer-supported experimental environment that enabled: (i) easy access to all data (on-line signals, laboratory measurements, batch parameters) needed for the design of the algorithm, (ii) the immediate application of the algorithm designed off-line in the Matlab™ package also in real-time control. When testing on the pilot plant, the control strategy demonstrated good agreement between the proposed completion times and actual terminations of the desired biodegradation processes.

Experimental design of an optimal phase duration control strategy used in batch biological wastewater treatment.

Hybrid modelling and optimal control of a Multiproduct Batch Plant

During the development of a production control system, an appropriate model of the production process is needed to evaluate the various control strategies. This paper describes how to apply timed Petri nets and existing production data to the modelling of production systems. Information concerning the structure of a production facility and the products that can be produced is usually given in production-data management systems. We describe a method for using these data to construct a Petri-net model algorithmically. The timed Petri-net simulator, which was constructed in Matlab, is also described. This simulator makes it possible to introduce heuristics, and, in this way, various production scenarios can be evaluated. To demonstrate the applicability of our approach, we applied it to a scheduling problem in the production of furniture fittings.

/pdf/production-process-modelling-based-on-production-management-momrpo3zcl.pdf

Gašper Mušič

Papers

Hybrid fuzzy model-based predictive control of temperature in a batch reactor

Original Articles: Coloured Petri net scheduling models: Timed state space exploration shortages

Experimental design of an optimal phase duration control strategy used in batch biological wastewater treatment.

Hybrid modelling and optimal control of a Multiproduct Batch Plant

Production-process modelling based on production-management data: a Petri-net approach