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Embedded Engineering + Control Engineering

• 20 h - Lectures (8h), tutorial class (4h), lab work (8h)

Coordinator: Denis Perret
Teacher: Denis Perret

Embedded Engineering

• Lectures:
  • From interconnected logic devices to programmed logic devices.
  • Embedded system design methodology, focus on the abstraction levels.
  • System description: introduction to VHDL description language.
  • What about microcontrollers and microprocessors: the IP (intellectual property) revolution.
• Tutorial:
  • Design of a simple 16-bits processor by using VHDL description.
• Lab work:
  • Basic examples of VHDL implementation on an FPGA.
  • Altera NIOS processor (or another): an example of using IP bloc.

Students should have some prerequisites about computer architecture, microcontroller concept and logic devices. Some lecture supports about these topics will be prepared and proposed before the start of this course.

Control Engineering

• linear systems, transfer functions
  • Laplace transform
  • transfer function
  • Fourier series
  • Fourier transform
• Frequency-domain analysis of linear systems
  • Bode plot
  • Nyquist plot
• Analysis of linear feed back systems
  • stability analysis: Routh-Hurwitz criterion, gain margin, phase margin
  • risetime, overshoot, velocity error, position error.
  • controllers: proportionnal, integral, derivative, phase correctors.
• Analysis of non linear systems (useful?)
  • saturation, hysteresis, harmonic balance…
• Analysis of discrete-time signals
  • Spectral analysis, Nyquist Shannon sampling theorem.
  • Z transform
  • Discrete-time equivalents to continous-time systems
• Stability and performance of discrete-time systems
  • stability criterions, position and velocity errors, dynamic performances.
• discrete-time control systems
  • pole placement
  • discretization of continous-time controllers
  • polynomial-based method
  • State-space representation of continuous-time systems
  • State variables
  • State-space equations
  • State-transition matrix
  • Controllability, observability
  • Relationship transfer function and state-space representation
• State-space representation of discrete-time systems
  • same as above but discrete-time
• State feedback control
  • principles, pole placement
  • observer, estimator, predictor
  • Kalman filter
  • Linear-quadratic-gaussian control.
• Tutorial:
  • Design of basic controllers.
• Lab work:
  • Matlab and simulink

Students should have some prerequisites in signal theory.