EE 5330 Distributed Decision & Control
Instructor: Frank L.
Lewis
Updated: Saturday, July 23, 2022 by F.L.
Lewis
This is a UTA Web-Based Course. �
Related webpages:
Systems and Controls Thrust Area
EE 5330 COURSE OUTLINE AND NOTES
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 5330 Distributed decision
& Control (3-0), 3 hours credit. Topics include multi-agent
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
Companies hiring
Control Engineers include Bell Flight, Ford Motors, Toyota Motors, Lockheed
Martin, Samsung, AT&T, Ericsson, American Airlines and Southwest Airlines.
Prerequisites: none. A knowledge of EE 5307 Linear Dynamical Systems is desirable.� EE 5307 notes are at EE SYSTEMS AND CONTROLS sequence
Course Objectives: To provide students with knowledge and abilities to analyze and design multi-agent 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 at
EE 5330 COURSE OUTLINE AND NOTES
Class hours: TuTh 330-450pm in NH 108
Instructor: F.L. Lewis, tel: 272-5972, office: UTARI room 215 (off campus), lewis@uta.edu
Faculty Profile https://www.uta.edu/profiles/dr-frank-lewis
Office hours: before or after class
Graduate Teaching
Assistant:� Bosen Lian bosen.lian@mavs.uta.edu
TA Office Hours:� TBA
Texts:
F.L. Lewis, H. Zhang, K. Hengster-Movric, A. Das, Cooperative Control of Multi-Agent Systems: Optimal and Adaptive Design Approaches, Springer-Verlag, 2014.
�
Grading:
Homework����������������������������������������������������������� 20%
Exam 1 (Take Home)������������������������������ 25%
Exam 2����������������������������������������������������� 30%
Final Project Report-������������������������������� 25%���� in
IEEE Format
The instructor reserves the right to make appropriate changes to the grading policy.
Submission of Homeworks and Posting of Solutions:
Homeworks and exams should be submitted to the
GTA through CANVAS online.� Solutions
will also be posted on CANVAS.
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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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.
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Arlington faculty members may employ the Honor Code in their courses by having
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