Sort by AttachmentsUse SHIFT+ENTER to open the menu (new window).
  1. Operations on fuzzy sets, fuzzy relations .
  2. Fuzzy connectives: t-norms, t-conorms, complements.
  3. Fuzzy Implications: S-implications, R-implications,
  4. Theory of approximate and fuzzy logic based reasoning.
  5. Fuzzy rule-based systems.
  6. Fuzzy reasoning for control:Mamdani/Sugeno.
  7. Examples.
  8. Clustering based objective system identification.
  9. Clustering examples.
Third Year
  1. Mathematical modeling of dynamic systems.
    Introduction, Transfer function and impulse response function, Automatic control systems
    Modeling in state space, State space representation of dynamic systems, Transformation of mathematical models with Matlab, Inverted pendulum system, Linearization of nonlinear mathematical models.
  2. Analysis of control system in state space.
    State space representation of canonical forms, transformation of system models with MATALB, Solving the time invariant state equation, vector matrix analysis, controllability, observability
  3. Design of control systems in state space.
    Pole placement, solving pole-placement-problems with Matlab, design of servo system, state observers, design of control systems with observers, quadratic optimal regulator systems
  4. Discrete time systems and the z-transform.
    Introduction, discrete-time systems, transform methods, properties of z-transform, the inverse z-transform simulation diagrams and flow graphs, state variables.
Third Year