In keeping with tradition, SSSC 2022 will feature both methodological contributions and application-oriented contributions. The theoretical topics will concern linear systems, time-varying systems, switching linear systems, impulsive systems, multidimensional systems, input-constrained systems, uncertain systems, positive systems, descriptor systems, complex systems, functional systems, fractional-order systems, network dynamics. The problems addressed will include decoupling, decentralized control, regulation, disturbance rejection, model matching, model reduction, output feedback control, observation, stability and stabilization, linearization-based control of nonlinear systems, robust control, diagnosis and fault tolerant control. Application-oriented domains will encompass automotive systems, aerospace, biological systems, biology, biotechnology, biomedical applications, chemical processes, energy and nuclear systems, mechanical systems, mechatronics, network controlled systems, power systems, process control, robotics, transportation systems, vibration and control. As a novelty of this edition, the scope of SSSC is extended to put a highlight on the rich connections between control theory and artificial intelligence. This interface is expected to provide fruitful and promising new research directions. Contributions at the cross section of these areas will be encouraged and experts will be actively involved in the conference program as authors, speakers, and organizers of thematic sessions. Further, since it is a special commitment to encourage young talents’ participation, innovative topics like this are expected to enhance the attractiveness of the symposium for the next generation of control scientists.
The TDS 2022 technical program will include contributed and invited papers as well as abstract submission, tutorial sessions and workshops, focusing on theoretical advances and technological applications of systems and control related to time delay systems. This focus includes but is not limited to modelling and identification, analysis, filtering and estimation, stability and stabilization, safety, structural properties, robustness, approximation techniques and numerical methods, data-driven and machine-learning methods, control schemes and application in process control, vibration control, networked systems, autonomous agents, communications, bio-engineering, economics and other fields. Particularly welcomed is the latest progress in emerging problem areas such as cyber-physical systems, artificial intelligence, cloud-based control, and in emerging applications such as smart grid, biomedical systems, intelligent transportation, intelligent manufacturing and automation.
LPVS’22 is an IFAC workshop aiming at presenting new results in the field of LPV systems and their applications in real life problems, by bringing together experts from different countries to discuss new trends, exchange new ideas, establish fruitful contacts, and promote interactions among the various fields of interest. The presentation of papers dealing with the application of the LPV models as well as LPV control strategies to practical setups and industry-issued papers are also strongly encouraged. The Workshop topics will cover the whole area for LPV systems: modelling, analysis, observation and control. In each one of these contexts, some of the important keywords include: Modelling and Identification of LPV systems. In particular, how to obtain LPV models for nonlinear systems, switching systems, time-delay systems, sampled-data systems, systems with saturation, uncertain systems, polynomial systems, etc; Analysis of LPV systems: stability and stabilization, robustness issues, geometric approaches, structural analysis, etc; Observation and diagnosis of LPV Systems: observer design, fault detection andsolation, etc; Control of LPV systems: robust control, optimal control, predictive control, constrained control, fault tolerant control, virtual reference feedback tuning, sampled-data control, event and selftriggered control, etc; Applications of LPV modeling and control: Aerospace, Autonomous systems, Automotive & Transport, Robotics, (Renewable) Energyr, biological and health systems, chemical processes, network-controlled-systems.