Linear Control

At the end of this learning unit, the student is able to :

• Model physical systems using both transfer function and state-space representations, with applications to mechanical, electrical, and process control systems.
• Analyze system properties such as stability, transient response, steady-state error, and robustness using time-domain and frequency-domain techniques.
• Translate design specifications into control specifications
• Apply classical control design techniques, such as PID control, root locus, Bode plots, and Nyquist criterion, to meet specifications.
• Design and analyze feedback control systems to ensure performance and robustness against disturbances, noise, and model uncertainties.
• Develop and use state-space models for the analysis of dynamic systems, including the assessment of controllability, observability, and internal stability.
• Synthesize state-feedback controllers and observers using, for example, pole placement and Linear Quadratic Regulator (LQR) methods.
• Translate control design problems into practical implementations using software tools (for example, MATLAB and Simulink, leveraging the Control System Toolbox).
• Solve practical control problems in lab settings, including fluid tank regulation, distillation process control, and robot control.
• Autonomously run automatic control experiments, from the design level to the actual implementation and performance evaluations.
• Communicate technical findings concisely through written reports and work in a team to develop control strategies in group settings.
• Demonstrate the ability to independently apply learned concepts to solve unseen control problems under time constraints.