EE 5329
Distributed Decision & Control
Updated: Thursday, December 25, 2014 by F.L. Lewis
This
is a UTA Web-Based Course. The internet
URL is http://www.uta.edu/utari/acs
Related
webpages:
Systems
and Controls Thrust Area
UT
Arlington Honor Code
I pledge, on my honor, to
uphold UT Arlington’s tradition of academic integrity, a tradition that values
hard work and honest effort in the pursuit of academic excellence.
I promise that I will only
submit work that I personally create or contribute to group collaborations, and
reference any work from other sources. I will follow the highest standards of
integrity and uphold the spirit of the Honor Code.
Information: EE
5329 Distributed decision & Control (3-0), 3 hours credit. Topics include cooperative decision
and control algorithms for networked teams of dynamical agents on communication
graphs. Included are local decision
protocols that yield global team behavior
Applications are to animal
behaviors such as swarms
Prerequisites: none. A knowledge of EE 5307 Linear Dynamical Systems is desirable.
Course Objectives: To provide students with knowledge and abilities to analyze and design distributed decision and control systems. To understand natural group synchronization in flocks, herds, schools, and physical and chemical systems. To understand the basic different types of graphs and the idea of phase transition, and their appearance in natural and manmade feedback systems. To lay a firm foundation in graph structure, Markov decision processes, and cooperative dynamical systems for future work. To understand local control protocols for consensus and synchronization of cooperative dynamical systems. To study formation control. Study graph routing problems, mean hitting times, and resistance distance. Study distributed decision, filtering, and estimation. To train students in the use of MATLAB for system design and simulation for the workplace.
Topics Covered: see separate schedule.
Class hours: TuTh 330-450pm in NH 229
Instructor: F.L. Lewis,
tel: 272-5972, office: ARRI room 215 (off campus), lewis@uta.edu
Office hours: before or after class
Teaching Assistant: Bahare Kiumarsi kiumarsi@uta.edu
Office hours: see Blackboard posting
Texts:
1. F.L.
Lewis, H. Zhang, K. Hengster-Movric, A. Das, Cooperative Control of Multi-Agent Systems: Optimal and Adaptive Design Approaches,
Springer-Verlag, 2014.
2. R. Diestel, Graph Theory, Springer, 2006
Grading:
Homework-- 20%
Exam 1 (take Home) Thur. 26 Feb 25%
Exam 2 (Take home) Thur 16 April 25%
Final Project Report- due Thur 7 May 30% in IEEE
Format
Student Learning Outcomes:
1. Understand natural group synchronization in flocks, herds, schools, and physical and chemical systems.
Assessment- homework design projects and examinations.
2. Understand the basic different types of graphs, the idea of phase transition, and graph structural properties
Assessment- homework design projects and examinations.
3. Ability to perform designs with various control tools using MATLAB computer simulation toolboxes.
Assessment- computer design and simulation projects assigned in homeworks.
4. Understand consensus and synchronization analysis and design in man-made cooperative dynamical systems.
Assessment- design and simulation projects in homeworks, exams.
5. Understand formations and their control, and potential field methods in distributed system coordination.
Assessment- design and simulation projects in homeworks, exams.
6. Understand the context of control systems design including the history of control and ethical responsibilities of engineers.
Assessment- general performance in class and final project report.
7. Learn to perform a survey and literature search and prepare a research paper with a unified presentation and exposition on a selected topic.
Assessment- Final Project Report.
Relation to Program Objectives. This course is motivated by recent
developments in the study and analysis of naturally occurring biological groups
such as herds
Attendance is not mandatory. If you skip classes, you will find the homework and exams more difficult. Due to the pace of the lectures, copying someone else's notes may be an unreliable way of making up an absence. You are responsible for all material covered in class regardless of absences.
You will need to use MATLAB, including the neural network, controls, and DSP toolbox. MATLAB is installed on the ACS network. Using the Student Edition of MATLAB you can install it on your own PC or MAC.
Check the grading of the exams thoroughly. You will have one week after the exam to see me for regrading. After this period, the grade is final.
Questions during class are strongly encouraged. The worst thing I can do is move too slowly and bore you. The next worst thing I can do is move too quickly and confuse you. If either of these occurs, it is your responsibility to speak up. You are paying for an education, and if the material is not presented clearly with confusion being eliminated shortly after it sets in you are not getting what you contracted for. On the other hand, if I never confuse you I am being unduly conservative and hence not conscientious. There is a very fine balance here, with you as student and me as instructor each having very definite responsibilities for keeping open all channels of communication. It is extremely difficult to teach a course without some sort of real-time feedback.
Some
philosophy. I have an attitude toward learning which is based very
heavily on independence and self-reliance; it can be
"Knowledge cannot be given, but comes only with great personal
sacrifice and effort."
It is my job to make knowledge available to you and show you one attitude toward it based on my experience in the area. It is your job to make it a part of yourself and so your own personal possession.
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Disabilities Act: The
University of Texas at Arlington is on record as being committed to both the
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with Disabilities Act (ADA). All instructors at UT Arlington are required
by law to provide "reasonable accommodations" to students with
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student requiring an accommodation for this course must provide the instructor
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students who have officially documented a need for an accommodation will have
their request honored. Information regarding diagnostic criteria and policies
for obtaining disability-based academic accommodations can be found at www.uta.edu/disability or by calling
the Office for Students with Disabilities at (817) 272-3364
Academic
Integrity: Students
enrolled in this course are expected to adhere to the UT Arlington Honor Code:
I pledge, on my
honor, to uphold UT Arlington’s tradition of academic integrity, a tradition
that values hard work and honest effort in the pursuit of academic excellence.
I promise that I will
submit only work that I personally create or contribute to group
collaborations, and I will appropriately reference any work from other sources.
I will follow the highest standards of integrity and uphold the spirit of the
Honor Code.
UT
Arlington faculty members may employ the Honor Code as they see fit in their
courses, including (but not limited to) having students acknowledge the honor
code as part of an examination or requiring students to incorporate the honor
code into any work submitted. Per UT System Regents’
Rule 50101, §2.2, suspected violations of university’s standards for
academic integrity (including the Honor Code) will be referred to the Office of
Student Conduct. Violators will be disciplined in accordance with University
policy, which may result in the student’s suspension or expulsion from the
University.
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Lab Safety Training is not required for this course.
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Final Review Week: A
period of five class days prior to the first day of final examinations in the
long sessions shall be designated as Final Review Week. The purpose of this
week is to allow students sufficient time to prepare for final examinations.
During this week, there shall be no scheduled activities such as required field
trips or performances; and no instructor shall assign any themes, research
problems or exercises of similar scope that have a completion date during or
following this week unless specified in
the class syllabus. During Final Review Week, an instructor shall not give
any examinations constituting 10% or more of the final grade, except makeup
tests and laboratory examinations. In addition, no instructor shall give any
portion of the final examination during Final Review Week. During this week,
classes are held as scheduled. In addition, instructors are not required to
limit content to topics that have been previously covered; they may introduce
new concepts as appropriate.
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Procedures: Should we experience an emergency event that requires us
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