14:332:415 - Introduction to Automatic Control Theory

Course Catalog Description: 

14:332:415 - Introduction to Automatic Control Theory (3)
The theory of automatically controlled systems and their dynamic behavior.

Pre-Requisite Courses: 

14:332:345

Pre-Requisite by Topic: 

1. Calculus
2. Ordinary differential equations
3. Complex variables
4. Linear system concepts

Textbook & Materials: 

Dorf, Modern Control Systems, 10th edition, Prentice Hall, 2005.

References: 

Ogata, Modern Control Engineering, 4th edition, Prentice Hall, 2002.

Overall Educational Objective: 

To develop skills, to analyze feedback control systems in both continuous- and discrete time domains and learn methods for improving system response transient and steady state behavior (response). Understand system stability concept and learn methods for examining system stability in both time and frequency domains including determining the system stability margins.

Course Learning Outcomes: 

A student who successfully fulfils the course requirements will have demonstrated:
- understanding of basic linear feedback principles.
- understanding of the feedback loop requirements such that the system steady state response is improved.
- an ability to determine conditions that guarantee the linear system stability
- an ability to design simple controllers via Bode plots such that the system stability margins are improved.
- an ability to understand to draw and understand Nyquist plots and find stability margins
- an ability to sketch the static feedback root locus and determine the location of the closed-loop poles.
- an ability to present and analyze linear control system using the state space technique

How Course Outcomes are Assessed: 

  • Two in-class exams (50%)
  • Project (20%)
  • Final exam (30%)

  • N = none S = Supportive H = highly related

    Outcome

    Level

    Proficiency assessed by

    (a) an ability to apply knowledge of mathematics, science, and engineering

    H

    Exams

    (b) an ability to design and conduct experiments and interpret data

    N

    (c) an ability to design a system, component or process to meet desired needs within realistic constraints such as economic, environmental, social, political, ethical, health and safety, manufacturability, and sustainability

    S

    (d) an ability to function as part of a multi-disciplinary team

    N

    (e) an ability to identify, formulate, and solve ECE problems

    H

    Project, exams

    (f) an understanding of professional and ethical responsibility

    N

    (g) an ability to communicate in written and oral form

    H

    project, exams

    (h) the broad education necessary to understand the impact of electrical and computer engineering solutions in a global, economic, environmental, and societal context

    N

    (i) a recognition of the need for, and an ability to engage in life-long learning

    S

    Discussions during lectures

    (j) a knowledge of contemporary issues

    N

    (k) an ability to use the techniques, skills, and modern engineering tools necessary for electrical and computer engineering practice

    H

    Exams, project

    Basic disciplines in Electrical Engineering

    H

    Exams

    Depth in Electrical Engineering

    H

    Exams

    Basic disciplines in Computer Engineering

    S

    MATLAB Simulations

    Depth in Computer Engineering

    N

    Laboratory equipment and software tools

    S

    MATLAB

    Variety of instruction formats

    S

    Lecture, office hour discussions

Topics Covered week by week: 

Week 1: System analysis tools such as LaPlace transforms, transfer function from system equations
Week 2: General modeling of dynamic systems
Week 3: Transient analysis
Week 4: Performance criteria, specifications
Week 5: Stability concept, Routh-Hurwitz Criterion
Week 6: Nyquist Criterion, Derivation, Examples
Week 7: Root Locus Method
Week 8: Examples, Midterm Examination
Week 9: Compensation Techniques involving root locus.
Week 10:Nichols and Halls chart, compensation examples
Week 11:Bode plots, compensation examples
Week 12:Introduction to sampled data systems
Week 13:Stability criterion, bilinear transformation
Week 14:Introduction to state space analysis; concepts of stability controllability and observability
Weeks 15: Review and Final Examination

Computer Usage: 

MATLAB is used to demonstrate control systems concepts and methods and for the project

Laboratory Experiences: 

The course is mostly analytical. However, students get also knowledge about designing elementary controllers.
A controller design project using MATLAB is assigned.

Independent Learning Experiences : 

Homework problems are assigned weekly with the solutions posted on the class website a week after. Homework problems are not graded, but the exams are based on homework. Students discuss homework solutions with the instructor during office hours

Contribution to the Professional Component: 

(a) College-level Mathematics and Basic Sciences: 0.5 credit hours
(b) Engineering Topics (Science and/or Design): 2.5 credit hours
(c) General Education: 0.0 credit hours
Total credits: 3

Prepared by: 
Z. Gajic
Date: 
May, 2011