ME511 MODERN CONTROL

Course Code:5690511
METU Credit (Theoretical-Laboratory hours/week):3 (3.00 - 0.00)
ECTS Credit:8.0
Department:Mechanical Engineering
Language of Instruction:English
Level of Study:Graduate
Course Coordinator:Prof.Dr. YİĞİT YAZICIOĞLU
Offered Semester:Fall and Spring Semesters.

Course Objectives

The main objective of this course is to introduce the basics of modern control systems to the students and to provide them with a background on the state variable approach necessary for further graduate courses on system dynamics, control, vibrations and robotics like ME 506ME 507ME 513, etc. offered in the department.


Course Content

Introduction. State space representation. Solution of the state equation. Controllability and observability Lyapunov stability. Controller design with state feedback. Observer design.


Course Learning Outcomes

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

  • interpret and apply the basic concepts of state space representation of multi-input multi-output (MIMO) dynamical systems, including
    • the concept of state
    • state and output equations
    • state controllability, state observability, output controllability
    • various state space representations for linear systems such as controllable canonical form, observable canonical form, diagonal canonical form and Jordan canonical form
    • decomposition of systems and minimal realizations
    • resolvent matrix and transfer function matrix
    • linear transformation between various state space representations
    • modal transformation;
  • correlate the time response of a linear system and its state transition matrix;
  • derive the state transition matrix of for a given system matrix;
  • obtain the time response of a time invariant or time varying MIMO system to a specified set of inputs and initial conditions, using its state transition matrix;
  • determine all equilibria for a given nonlinear system;
  • demonstrate their understanding of various stability definitions;
  • analyze the stability of a linear or nonlinear system about an equilibrium point using Lyapunov approach;
  • design linear state feedback controllers, for the purpose of
    • pole assignment using state feedback,
    • decoupling via state feedback,
    • obtaining optimal feedback coefficients for linear quadratic regulators;
  • design state observers, including
    • full order observers
    • reduced order observers.