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    M.SC. in Computer Engineering (With Thesis)

    EEE 512 | Course Introduction and Application Information

    Course Name
    Optimal Control
    Code
    Semester
    Theory
    (hour/week)
    Application/Lab
    (hour/week)
    Local Credits
    ECTS
    EEE 512
    Fall/Spring
    3
    0
    3
    7.5

    Prerequisites
    None
    Course Language
    English
    Course Type
    Elective
    Course Level
    Second Cycle
    Mode of Delivery -
    Teaching Methods and Techniques of the Course -
    National Occupation Classification -
    Course Coordinator
    Course Lecturer(s) -
    Assistant(s) -
    Course Objectives The course aims the students: i) to get a solid mathematical background on derivations of optimality conditions for constrained and unconstrained static optimization problems with optimal control problems and ii) to gain skills on finding optimal solutions of a static cost function and a given performance index for a linear time-invariant dynamical system by analytical and numerical methods.
    Learning Outcomes

    The students who succeeded in this course;

    • Derive optimality conditions for constraint and unconstrained optimization problems
    • Use numerical solution methods for finding minima of static optimization problems
    • Derive optimality conditions for optimal control of discrete-time and continuous-time linear time-invariant dynamical systems
    • Obtain analytical and numerical solutions for linear quadratic regulator, steady state closed loop control and tracking control problems.
    Course Description Static optimization with and also without constraints. Optimality conditions. Lagrange multipliers. Karush-Kuhn-Tucker conditions. Steepest-descent and Newton methods. Calculus of variations. Optimal control of discrete time and continuous time systems. Linear quadratic regulator, steady state closed loop control and tracking control. Dynamic programming of both discrete time and continuous time systems.

     



    Course Category

    Core Courses
    Major Area Courses
    Supportive Courses
    Media and Management Skills Courses
    Transferable Skill Courses

     

    WEEKLY SUBJECTS AND RELATED PREPARATION STUDIES

    Week Subjects Related Preparation Learning Outcome
    1 Optimality conditions for single variable static optimization. Frank L. Lewis, Vassilis Srimos, Optimal Control, Second edition, John Wiley & Sons, 1995
    2 Optimality conditions for multi variable static optimization Frank L. Lewis, Vassilis Srimos, Optimal Control, Second edition, John Wiley & Sons, 1995
    3 Constrained optimization, Lagrange multipliers, Karush-Kuhn-Tucker conditions. Frank L. Lewis, Vassilis Srimos, Optimal Control, Second edition, John Wiley & Sons, 1995
    4 Numerical methods for static optimization. Frank L. Lewis, Vassilis Srimos, Optimal Control, Second edition, John Wiley & Sons, 1995
    5 Variational calculus. Frank L. Lewis, Vassilis Srimos, Optimal Control, Second edition, John Wiley & Sons, 1995
    6 Optimality conditions for optimal control problems defined as the minimization of a performance index under the given system’s state equations constraints. Frank L. Lewis, Vassilis Srimos, Optimal Control, Second edition, John Wiley & Sons, 1995
    7 Solutions of free initial state, fixed initial state, free final state and fixed final state problems. Frank L. Lewis, Vassilis Srimos, Optimal Control, Second edition, John Wiley & Sons, 1995
    8 Optimal control problems, minimum time and minimum fuel problems. Frank L. Lewis, Vassilis Srimos, Optimal Control, Second edition, John Wiley & Sons, 1995
    9 1. Midterm
    10 Linear quadratic regulator problem. Frank L. Lewis, Vassilis Srimos, Optimal Control, Second edition, John Wiley & Sons, 1995
    11 Solving Riccati equation, Kalman gain. Frank L. Lewis, Vassilis Srimos, Optimal Control, Second edition, John Wiley & Sons, 1995
    12 Tracking problem for linear time-invariant systems. Frank L. Lewis, Vassilis Srimos, Optimal Control, Second edition, John Wiley & Sons, 1995
    13 2. Midterm
    14 Steady-state closed-loop control problem for linear time-invariant systems. Frank L. Lewis, Vassilis Srimos, Optimal Control, Second edition, John Wiley & Sons, 1995
    15 Dynamical programming. Frank L. Lewis, Vassilis Srimos, Optimal Control, Second edition, John Wiley & Sons, 1995
    16 Review of the Semester  

     

    Course Notes/Textbooks The textbook referenced above and lecture notes
    Suggested Readings/Materials Related Books

     

    EVALUATION SYSTEM

    Semester Activities Number Weigthing
    Participation
    Laboratory / Application
    6
    60
    Field Work
    Quizzes / Studio Critiques
    Portfolio
    Homework / Assignments
    Presentation / Jury
    Project
    2
    40
    Seminar / Workshop
    Oral Exams
    Midterm
    Final Exam
    Total

    Weighting of Semester Activities on the Final Grade
    8
    100
    Weighting of End-of-Semester Activities on the Final Grade
    Total

    ECTS / WORKLOAD TABLE

    Semester Activities Number Duration (Hours) Workload
    Theoretical Course Hours
    (Including exam week: 16 x total hours)
    16
    3
    48
    Laboratory / Application Hours
    (Including exam week: '.16.' x total hours)
    16
    2
    32
    Study Hours Out of Class
    15
    4
    60
    Field Work
    0
    Quizzes / Studio Critiques
    0
    Portfolio
    0
    Homework / Assignments
    0
    Presentation / Jury
    0
    Project
    2
    42
    84
    Seminar / Workshop
    0
    Oral Exam
    0
    Midterms
    0
    Final Exam
    0
        Total
    224

     

    COURSE LEARNING OUTCOMES AND PROGRAM QUALIFICATIONS RELATIONSHIP

    #
    PC Sub Program Competencies/Outcomes
    * Contribution Level
    1
    2
    3
    4
    5
    1 Accesses information in breadth and depth by conducting scientific research in Computer Engineering; evaluates, interprets and applies information.
    -
    -
    -
    -
    -
    2 Is well-informed about contemporary techniques and methods used in Computer Engineering and their limitations.
    -
    -
    -
    -
    -
    3 Uses scientific methods to complete and apply information from uncertain, limited or incomplete data; can combine and use information from different disciplines.
    -
    -
    -
    -
    -
    4 Is informed about new and upcoming applications in the field and learns them whenever necessary.
    -
    -
    -
    -
    -
    5 Defines and formulates problems related to Computer Engineering, develops methods to solve them and uses progressive methods in solutions.
    -
    -
    -
    -
    -
    6 Develops novel and/or original methods, designs complex systems or processes and develops progressive/alternative solutions in designs
    -
    -
    -
    -
    -
    7 Designs and implements studies based on theory, experiments and modelling; analyses and resolves the complex problems that arise in this process.
    -
    -
    -
    -
    -
    8 Can work effectively in interdisciplinary teams as well as teams of the same discipline, can lead such teams and can develop approaches for resolving complex situations; can work independently and takes responsibility.
    -
    -
    -
    -
    -
    9 Engages in written and oral communication at least in Level B2 of the European Language Portfolio Global Scale.
    -
    -
    -
    -
    -
    10 Communicates the process and the results of his/her studies in national and international venues systematically, clearly and in written or oral form.
    -
    -
    -
    -
    -
    11 Is knowledgeable about the social, environmental, health, security and law implications of Computer Engineering applications, knows their project management and business applications, and is aware of their limitations in Computer Engineering applications.
    -
    -
    -
    -
    -
    12 Highly regards scientific and ethical values in data collection, interpretation, communication and in every professional activity.
    -
    -
    -
    -
    -

    *1 Lowest, 2 Low, 3 Average, 4 High, 5 Highest

     


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