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19D051SDMU - Distributed Sensing and Control Systems

Course specification
Course title Distributed Sensing and Control Systems
Acronym 19D051SDMU
Study programme Electrical Engineering and Computing
Module System Control and Signal Processing
Type of study doctoral studies
Lecturer (for classes)
Lecturer/Associate (for practice)
    Lecturer/Associate (for OTC)
      ESPB 9.0 Status elective
      Condition None.
      The goal Introduce students to principles of distributed sensing and control, enabling technologies and available techniques for design and implementation of such systems.
      The outcome Students are able to: define appropriate design and implementation framework for distributed system application, define and implement sensing and/or control functionalities on either conceptual or concrete level.
      Contents
      Contents of lectures Introduction. Integration of control, communications and computing. Architectures and technology support. Network-enabled and resource-constrained systems. Stability and optimization. Distributed algorithms and control: predictive, quadratic-optimal, consensus, estimation and filtering. Applications: industry, smart grid, home automation, precision agriculture and complex cyber-physical systems.
      Contents of exercises None.
      Literature
      1. M. Mahmoud, Distributed control and filtering for industrial systems, IET, 2013. (Original title)
      2. A. Çela, M. Ben Gaid and G. Li, Optimal Design of Distributed Control and Embedded Systems, Springer, 2014. (Original title)
      3. J. Rawlings and D. Mayne, Model predictive control, Nob Hill Publishing, 2009. (Original title)
      4. H. Rashvand and J. Alcaraz Calero, Distributed sensor systems, Distributed sensor systems, Wiley, 2012. (Original title)
      5. A. Tanenbaum and M. Steen, Distributed systems, Prentice Hall, 2007. (Original title)
      Number of hours per week during the semester/trimester/year
      Lectures Exercises OTC Study and Research Other classes
      8
      Methods of teaching Lectures. Students are obliged to solve and defend individually assigned project, which earns them exam points.
      Knowledge score (maximum points 100)
      Pre obligations Points Final exam Points
      Activites during lectures Test paper
      Practical lessons Oral examination 30
      Projects 70
      Colloquia
      Seminars