Invited sessions

Complex service modelling, composition, and engineering (code: f76rx)

Monica Drăgoicea, University Politehnica of Bucharest, monica.dragoicea(#at#)
Michel Léonard, University of Geneva, Michel.Leonard(#at#)
Adrian Paschke, Fraunhofer FOKUS, adrian.paschke(#at#)

Keywords: service systems engineering, complex systems, complex service, digital technologies, artificial intelligence

Service, the law of interaction among the large number of Society-level entities, grounded on data, supports the creation of value via information interactions fundamentally.  A complex service is built upon several services, and its systems, including its digital system, are composed upon their systems. Therefore, the information is an important source of innovation, and the Digital means enable to introduce new functionalities which were difficult or impossible to offer before. Technology, as an operant resource, leverage information sharing across service ecosystems at Society level, enabling data-driven value co-creation as a service strategy.

This session is inviting original submissions addressing the entire development cycle of complex services and their service systems, enacting new types of knowledge exchange that would advance Society in its complexity. Society is facing today critical situations for which its systems must be purposely reshaped. Complexity, a fundamental characteristic of the world we live in, must be understood against Society needs and new tools for analyzing and describing it are required today.

Authors are encouraged as well to present developed practices, mechanisms, methods, toward increasing the engagement in teaching, learning, research and institutional activities to support digital skills formation in industry fostering new services and jobs creation. In this perspective, it concerns important properties of Service Science, which induce situations where knowledge, skills, activities and jobs can emerge to surmount challenges in identifying the growing share of increasingly complex services that characterize the digital economy.

Advanced topics in chemical process control: resilience, optimization and decision-making systems (code: wq2y2)

Emil Pricop, Petroleum-Gas University of Ploiesti, emil.pricop(#at#)
Sanda Florentina Mihalache, Petroleum-Gas University of Ploiesti, sfrancu(#at#)
Nicolae Paraschiv, Petroleum-Gas University of Ploiesti, nparaschiv(#at#)
Jaouhar Fattahi, Laval University, jaouhar.fattahi.1(#at#)

Keywords: control systems design, industrial applications, fault diagnosis and fault tolerant control

This invited session aims at designing and analyzing high-performance resilient control systems for chemical processes. The topic is one of high importance nowadays since chemical processes are the core of a large number of critical infrastructures such as refineries, petrochemical and pharmaceutical plants or wastewater processing facilities. These infrastructures are supposed to function without error and any interruptions for significant periods of time. This goal can be achieved only if the supporting infrastructure is reliable and the control systems are more secure, reliable, maintainable and performant than the controlled infrastructure.

In other words, the next generation of control systems should be designed to keep their normal operation in response to any disturbances, being them operational errors, unexpected malfunctions or malicious threats.

The invited session focuses on, but is not limited to the following topics: resilience of control systems in critical infrastructures, resilient chemical process control, advanced chemical process control, control systems security, optimal control systems, decision-making systems, machine learning applications for resilient chemical process control.

Real time applications for process control and diagnosis (code: 5h8w1)

Dumitru Popescu, University Politehnica of Bucharest, dumitru.popescu(#at#)
Ciprian Lupu, University Politehnica of Bucharest, ciprian.lupu(#at#)

Keywords: control systems design, industrial applications, fault diagnosis and fault tolerant control

The session offers a framework for presentations of research that bring interesting and relevant contributions in the field of adaptive, predictive or robust control and system diagnosis.

The session provides opportunities for researchers and specialists to offer their recent developments in control and diagnosis, applied to different domains with technical and economical interest as, for example: Energy, Transport, Automotive, Petrochemistry, Aerospace, Biotechnology, Telecommunications, etc. We evaluate and discuss during this session about performance and security issues that arise in process exploitation and about fault detection and management in real-time applications, by means of automatic control resources and information support.

Appreciated papers should offer modern solutions related to the modeling, control and diagnosis of systems structures, supported by an adequate theoretical background, implemented and validated on industrial applications.

Complex autonomous systems for assisted living and manufacturing (code: 66x9c)

Adrian Filipescu, “Dunarea de Jos” University of Galati, adrian.filipescu(#at#)
Daniela Cristina Cernega, “Dunarea de Jos” University of Galati, daniela.cernega(#at#)
Razvan Solea, “Dunarea de Jos” University of Galati, razvan.solea(#at#)

Keywords: robotics, manufacturing systems, hybrid systems

Complex Autonomous Systems (CAS) have a wide applicability, mainly in medical-social assistance and flexible manufacturing. They are mobile robotic platforms equipped with manipulator integrated into technologies for personal assistance and service of precision flexible manufacturing lines for reusable products. We propose the following types of complex autonomous systems, but not limited to them: Intelligent Wheelchair (CAS-IW) for people with severe disabilities. Assistance and navigation technologies are video-biometric; Personal Robotic Assistant (CAS-PRA) is an autonomous robotic platform with manipulator. Assistance technology is made for the elderly and disabled, in hospital or at home. The main capabilities are: obstacle avoidance navigation, locomotory, sensory, cognitive prosthesis, medical parameters monitoring, voice command recognition. Multidirectional Autonomous Vehicle (CAS-MAV) with 4 driving multidirectional wheels with manipulator, has an assistive technology capable of: transportation, towing medical stretcher, in/out door hospital and rescue on rough terrain. At CAS-PRA and MAV, the control and navigation structure is based on advanced control, ultrasound, laser and visual serving systems to avoid obstacles, localisation and manipulation. CAS-PRA and CAS-MAV could be integrated in manufacturing technologies, on assembly and processing laboratory (mechatronics) lines and/or industrial lines. Thus, the lines become reversible and/or flexible.

This invited session welcomes papers addressing the following areas: Advanced Perception, Localization and Control of Robots; Robot Vision; Cognitive Computing for Robots; Agent Based Manufacturing Systems; Holonic Manufacturing System; Complex Manipulation; Adaptive Flexible Automation.

Bioprocess systems control (code: xhe3g)

George Ifrim, “Dunarea de Jos” University of Galati, george.ifrim(#at#)
Mariana Titica, University of Nantes, Mariana.Titica(#at#)
Ramon Vilanova, Autonomous University of Barcelona, ramon.vilanova(#at#)
Marian Barbu, “Dunarea de Jos” University of Galati, marian.barbu(#at#)

Keywords: nonlinear systems, control systems design, system identification and modeling

The biotechnological processes have a great potential in developing different industries in order to produce useful substances for the benefit of human activities. The biotechnologies are applied in different domains such as food, pharmaceutics, medicine, energy producing (biofuels), depollution (wastewater treatment, CO2 mitigation), etc. Currently, two research directions are addressed by the academic communities in the field: the development of new technologies and the application of the automation methods to increase the efficiency of biotechnologies. The second research direction has led the biotechnologists and specialists towards interdisciplinary approaches in modeling and control. Practically, the modeling and the control of the bioprocesses has become a real challenge for automatists as a result of their complexity; bioprocesses are strongly affected by non-linearities, parametric and model uncertainties, the lack of some reliable and cost-effective sensors, etc.

In this context, the proposed invited session aims at stimulating interactions between researchers, scientists and engineers from academia and industry, so as to share knowledge and experience in the area of the control and the automation of processes involving living organisms. Contributions where mathematical modelling and control theory are used in (bio)process design, monitoring, optimization and control are welcomed. Theoretical and practical studies are equally encouraged.

Complex data processing for monitoring, diagnosis, and control (code: im2ig)

Dan Popescu, University Politehnica of Bucharest, dan_popescu_2002(#at#)
Loretta Ichim, University Politehnica of Bucharest, iloretta(#at#)
Corneliu Lazar, Gheorghe Asachi Technical University of Iasi, clazar(#at#)

Keywords: signal processing, computer vision, control systems design

The session aims to underline the intrinsic connection between complex data processing, on one hand, and two important actions in different fields: monitoring and control, on the other hand. The applications of complex images (like texture and fractals), time series, and neural networks in many domains (like: industry, medicine, agriculture, environment, transportation, and so on) needs interdisciplinary knowledge and effectively solve many encountered problems. This special session at the 23rd International Conference on System Theory, Control and Computing (ICSTCC 2019) provides a forum for researchers and practitioners to present and discuss advances in the research and development of intelligent systems for complex data processing and interpretation based on efficient feature selection and neural networks in the field of monitoring, control and diagnosis. All session papers need to have a high scientific level and will be selected based on their relevance to the session topics.

The included topics are the following (but not limited): Criteria for feature selection, Image processing for real time control, Traffic control based on images, Medical diagnostic systems based on complex data processing, Assistive technologies based on data processing, UAV and robot guidance based on image interpretation, Quality control based on image processing, Fractal analysis, Texture analysis, Parallel processing of data, Neural networks for data classification and prediction. Papers submitted for a special session will be treated in the same manner as the regular papers.