Digital Control & System Identification
This course covers digital control theory and system identification, focusing on design, analysis, and optimization.
Digital Control: Explores discrete transfer functions, state-space representation, stability analysis, and PID-based control in the discrete domain, with applications in mobile robotics.
System Identification: Covers measurement techniques, statistical modeling, parametric/non-parametric methods (ARX, OE), gradient-based optimization, and recursive estimation.
Students gain practical skills in designing digital controllers and identifying system models, preparing them for real-world control applications.
G1: Translate mechatronics systems and robots into mathematical models and simulations.
G2: Critically evaluate robotic systems in comparison with state-of-the-art robotic research.
G4: Develop, test, and integrate robotics hardware and software into fully functional systems.