Advanced control - 3EM6AUA6

Goal(s)

At the end of the course, students will be able to:

• Model a dynamical system in state-space form
• Assess its controllability and observability
• Design a state-feedback controller
• Construct a state observer (Luenberger)
• Understand the fundamentals of optimal control (LQR)

Responsible(s)

Nacim MESLEM

Content(s)

• Review of continuous-time linear systems
• From input-output representation to state-space form
• Concept of state variables
• Solution of the state-space system
• State transition matrix
• Internal stability (eigenvalues)
• Controllability: definition and interpretation
• Kalman criterion
• State-feedback control: principle
• Pole placement
• Physical interpretation
• Gain computation methods
• Observability: definition and interpretation
• Kalman criterion
• Luenberger observer: principle (state estimation)
• Estimation error dynamics
• Observer gain design (pole placement)
• Control with observer: full loop (state-feedback using estimated states)
• Separation principle
• Overall architecture
• Introduction to optimal control: motivation (performance/energy trade-off)
• Quadratic cost function
• Riccati equation
• Optimal state-feedback gain
• Comparison with pole placement

• Linear algebra (matrices, eigenvalues)
• Basic control theory (transfer functions, stability)
• Differential equations

Test

Calendar

The course exists in the following branches:

• Curriculum - Master's Degree in Engineering SEM - Semester 6

Additional Information

Course ID : 3EM6AUA6
Course language(s):

You can find this course among all other courses.