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    EE 550 Linear Control Systems

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    deraliker
    This document provides information about the EE 550 Linear Control Systems course taught by Professor Samir A. Al-Baiyat in spring 2006-2007. The key aspects of the course include studying linear multivariable systems through modeling and analysis of both continuous-time and discrete-time systems. The course outline covers topics such as mathematical descriptions of systems, state space solutions, stability, controllability, observability, and minimal realizations. Assessment includes homework, a project, a major exam, and a final exam.

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    EE 550 Linear Control Systems

    Uploaded by

    deraliker
    24 views11 pages
    This document provides information about the EE 550 Linear Control Systems course taught by Professor Samir A. Al-Baiyat in spring 2006-2007. The key aspects of the course include studying linear multivariable systems through modeling and analysis of both continuous-time and discrete-time systems. The course outline covers topics such as mathematical descriptions of systems, state space solutions, stability, controllability, observability, and minimal realizations. Assessment includes homework, a project, a major exam, and a final exam.

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    lecture control system

    Original Title

    Lecture 550-1 062

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    This document provides information about the EE 550 Linear Control Systems course taught by Professor Samir A. Al-Baiyat in spring 2006-2007. The key aspects of the course include studying linear multivariable systems through modeling and analysis of both continuous-time and discrete-time systems. The course outline covers topics such as mathematical descriptions of systems, state space solutions, stability, controllability, observability, and minimal realizations. Assessment includes homework, a project, a major exam, and a final exam.

    Copyright:

    © All Rights Reserved
    Download as PPT, PDF, TXT or read online from Scribd
    Download as ppt, pdf, or txt
    24 views11 pages

    EE 550 Linear Control Systems

    Uploaded by

    deraliker
    This document provides information about the EE 550 Linear Control Systems course taught by Professor Samir A. Al-Baiyat in spring 2006-2007. The key aspects of the course include studying linear multivariable systems through modeling and analysis of both continuous-time and discrete-time systems. The course outline covers topics such as mathematical descriptions of systems, state space solutions, stability, controllability, observability, and minimal realizations. Assessment includes homework, a project, a major exam, and a final exam.

    Copyright:

    © All Rights Reserved
    Download as PPT, PDF, TXT or read online from Scribd
    Download as ppt, pdf, or txt
    of 11

    EE 550

    Linear Control Systems

    Professor Samir A. Al-Baiyat


    Spring 2006 – 2007
    Course Information

    OFFICE: 16-149
    PHONE: 860 2500
    EMAIL: sbaiyat@kfupm.edu.sa
    OFFICE HRS: Sat, Mon., 11:00-12:00 or by appt.
    GRADING: Homework 15%
    Project 20%
    Major Exam 25%
    Final Exam 40%
    INFORMATION: http://webcourses.kfupm.edu.sa
    TEXTBOOK Linear System Theory and Design, 3rd
    Edition, C. T. Chen

    References
    • Linear System, Panos Antsaklis and Anthony Michel
    • Linear System, Thomas Kailath
    • Linear System Theory, W. Rugh

    EXAMINATIONS:
    Major Exam: Monday April 9, 2007
    Final Exam: Wednesday June 6, 2007
    Course Objective:
    This course provides a basic understanding of
    linear multivariable systems through their modeling
    and analysis. Both continuous-time and discrete-
    time systems will be discussed in the course. After
    taking this course, the student will be in a position
    to move on to more advanced courses and topics
    in systems, control, communications and signal
    processing.
    TENTATIVE COURSE OUTLINE

    •Overview
    •Mathematical Description of Systems
    – Input-Output Description
    – State-Variable Description
    •State Space Solutions and Realization
    •Stability of Linear Systems
    •Controllability and Observability
    •Canonical Decompostion
    •Minimal Realizations
    •State Feedback and State Estimators
    •Other Topics as Time Allows
    The Study of Systems
    Systems: It is a medium that relates a cause to an
    effect, or an input to an output.
    The study and design of physical systems often
    consists of:
    1. Performance specifications
    2. Modeling
    3. Simulations
    4. Analysis
    5. Optimization
    6. Physical Realization
    Modeling is the representation of a system and
    all its components in a mathematical form.

    Depending on the questions asked, or


    depending on the operating ranges, a physical
    system may have different models

    Example: An Automobile may be modeled as a


    single particle if we are studying traffic flow but
    may be modeled as a spring-mass-damper
    system if we are interested in the vibration of the
    occupants
    • Once a model is selected for a physical
    system, the next step is to develop
    mathematical equations to describe the
    system from the fundamental physical
    principles such as:

    • Newton’s law for mechanical systems


    • Kirchhoff’s voltage and current laws in
    electrical systems
    • Laws of thermodynamics and transport
    phenomena in fluid and thermal systems
    • After the mathematical equations for the
    model have been obtained the next step in
    the study of systems involves both

    • Quantitative
    – System responses to specified inputs

    • Qualitative
    – Stability
    – Controllability
    – Observability
    – If the response of the system is found to be
    unsatisfactory then an engineering design phase
    termed improvement or optimization is initiated

    – In some cases a system parameter may be adjusted


    to improve the response but in other cases
    compensation devices must be injected into the
    system

    – Finally in the realization phase the proposed system


    must be built using actual physical hardware
    System Classification

    System Classes

    Distributed Lumped
    Parameter

    Stochastic Deterministic

    Continuous Discrete
    Time Time

    Nonlinear Linear Nonlinear Linear

    Time Varying Time Invariant

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