- Teacher: Χαράλαμπος Σαρίμβεης
ECTS : 7
Language : el
Learning Outcomes : Upon successful completion of the course, the student will be able to: • Describe the basic concepts related to modeling and regulation of systems with state-space models. • Construct state-space models for physical systems and convert them to canonical form. • Apply transformations of dynamic models into different forms (differential equations, transfer functions, state-space systems). • Explain the concepts of controllability and observability. • Construct simulations of state-space systems in different open-loop or closed-loop scenarios. • Apply the Lyapunov method for investigating the stability of state-space systems. • Compare three different methodologies for designing controllers for state-space systems based on pole placement. • Understand basic concepts of optimal control as well as the steps leading to the formulation of the LQR methodology. • Design multivariable controllers using the LQR method. • Understand methodologies for discretization of dynamic systems. • Design predictive control systems based on discrete dynamic models.