ABOUT LEAN CELL ADVISING

Students must sign up for a 30-minute block using iAdvise to prevent long wait times. All advising sessions will be held in Rawl Engineering Practice Facility, Room 200. When students arrive, they should have completed all tasks under “Know Before You Go” below.

All students must attend Lean Cell Advising or students may not be able to enroll in courses until Fall 2017. 

LEAN CELL ADVISING + iADVISE

AME Students must sign up for advising with iAdvise. AME has designated a 30-minute block sign up for students. The appointment should only take approximately 10-15 minutes as long as student comes prepared. Please note, all students MUST SIGN-UP FOR A TIME WITH iADVISE IN ORDER TO BE ADVISED.

Follow the simple steps below to sign-up with iAdvise:

  1. Log in to http://iadvise.ou.edu using your 4×4 and password.
  2. Select the Department Level Advisement (AE or ME at the School of Aerosapce and Mechanical Engineering), then select Make Group Appointment. 
  3. Reserve an advising time slot (ex. 12:30 time is for 12:30-1:00pm time slot). You can only reserve one slot.
  4. Arrive at the beginning of your time slot. You will be seen sometime within that 30-minute time frame. The advising session should only take approximately 10-15 minutes if student comes prepared.
  5. If you do not reserve a time slot before attending Lean Cell Advising, you may not be seen if the time slot is full.
iAdvise
download icon iAdvise Step-by-Step
Download the iAdvise step-by-step PDF here:

ADVISING DATES

All AME Lean Cell Advising sessions will take place in the Rawl Engineering Practice Facility, Room 200.

  • Returning Seniors & National Merit Scholars: Tuesday, February 28th from 12:00-3:00pm
  • Sophomores & Pre-Med: Wednesday, March 1st from 1:00-4:00pm
  • Juniors: Thursday, March 2nd from 12:00-3:00PM
  • Freshmen: Monday, March 27th from 1:00-4:30PM

Unsure of your academic classification? Go to oZone > click the academic tab > click academic profile > select the current semester

KNOW BEFORE YOU GO

  • Prepare a course plan in Degree Navigator by logging on to ozone.ou.edu (The course plans on oZone do not check for pre-requisites nor will it verify courses offered during a specific semester)
  • Bring prepared course plan, degree check sheet and degree flowchart with the classes you have taken checked off, current courses circled and courses you plan to take in Fall 2017 highlighted
  • If you are not prepared upon arrival, your time will not be guranteed
  • A staff member from the Williams Student Services Center will be in attendance to remove your advising hold and answer any enrollment/graduation questions
  • A Pre-Med representative will be in attendance on Wednesday, March 1st

OTHER INFORMATION

Freshmen are required to be advised by their University College, Athletics, or Honors/Scholars Advisor in order to be able to enroll.

Do you have questions or concerns about advising, classes, your current major or school in general?

Please know that aside from Lean Cell Advising, you are encouraged to meet with your College Advisor in the Williams Student Services Center (WSSC) any time you have questions, or concerns you wish to discuss in a one-on-one meeting. Lean Cell Advising is an advising process intended to provide a stream-lined process for meeting with your major faculty advisor while also addressing the multiple steps in theadvising/enrollment system without having to visit multiple offices and staff. HOWEVER, you can, and are encouraged to, meet with your WSSC advisor if you require or would benefit from more in-depth guidance and academic counseling. It’s easy to do! Log into: iadvise.ou.edu to access available appointment times for your specific advisor. Don’t see any openings? Click here to contact your WSSC advisor or call WSSC directly at (405) 325-4096.

Do you have questions about career fairs, graduate school, internships and co-ops? 

WSSC advisors are here to assist you with Career Counseling. We encourage you to take advantage of this guidance as you prepare for your future as an engineer!

QUESTIONS?

For more information or accommodations on the basis of disability, please contact Kate O’Brien at kobrien@ou.edu.

Dr. David P. Miller spoke at the 2017 Oklahoma City Joint Engineering Societies Banquet on February 23, 2017 at the Gaylord Student Center at Oklahoma Christian University in Edmond, Oklahoma.

The program featured Dr. David P. Miller, who since 1999 has been the Wilkonson Chair and Professor of Intelligent Systems based in the School of Aerospace and Mechanical Engineering (AME) at the University of Oklahoma. Miller has a Bachelors in Astronomy from Wesleyan University and a Ph.D. in Computer Science/AI from Yale. His primary research areas are in mobility, the tradeoff between algorithm and mechanism, assistive technology and STEM education. Miller worked at NASA’s Ames Research Center and the Jet Propulsion Laboratory, and was awarded the NASA Exceptional Service Medal for his work at JPL leading to the Mars Pathfinder Rover Mission. He is a founder of KISS Institute for Practical Robotics and their Botball Program. Miller is the faculty advisor for the OU Boomer Rocket Team and the Sooner Rover Team (SoRo). In the Fall of 2015, OU was competitively selected as one of eight universities to compete in the NASA RASC-AL Robo-Ops competition. The competition involves finding and retrieving designated samples from Mars and Lunar-like environments (at NASA JSC) while tele-operating the rover from a remote location (in our case, Norman OK). OU students designed and built the rover over the next 8 months and competed in May of 2016. This talk will discuss the team, their design and performance at the competition (Spoiler: we won).

According to Miller, after his “Rovers and OU Student Engineering Teams” presentation, several high school students that plan to attend the University of Oklahoma expressed interest in joining rover, rocket or space related student teams and were currently involved in robotics teams at their high school.

The Oklahoma Society of Professional Engineers (OSPE) Central/Southwest Chapter sponsored the banquet. This event was held in conjunction with Engineer’s Week that many Oklahoma engineering societies participate in. A number of students also attended the banquet, including participants in Engineer for a Day, Future Ciies, and MATHCOUNTS programs.

andrea-lafflitto-a-mathematical-perspective-on-flight-dynamics-and-control-book

 

Dr. Andrea L’Afflitto has recently published a new book titled A Mathematical Perspective on Flight Dynamics and Control. The book provides a mathematically rigorous description of flight dynamics complementing those presented from a physical perspective.

About this Book

This brief presents several aspects of flight dynamics, which are usually omitted or briefly mentioned in textbooks, in a concise, self-contained, and rigorous manner. The kinematic and dynamic equations of an aircraft are derived starting from the notion of the derivative of a vector and then thoroughly analyzed, interpreting their deep meaning from a mathematical standpoint and without relying on physical intuition. Moreover, some classic and advanced control design techniques are presented and illustrated with meaningful examples.

Distinguishing features that characterize this brief include a definition of angular velocity, which leaves no room for ambiguities, an improvement on traditional definitions based on infinitesimal variations. Quaternion algebra, Euler parameters, and their role in capturing the dynamics of an aircraft are discussed in great detail. After having analyzed the longitudinal- and lateral-directional modes of an aircraft, the linear-quadratic regulator, the linear-quadratic Gaussian regulator, a state-feedback H-infinity optimal control scheme, and model reference adaptive control law are applied to aircraft control problems. To complete the brief, an appendix provides a compendium of the mathematical tools needed to comprehend the material presented in this brief and presents several advanced topics, such as the notion of semistability, the Smith–McMillan form of a transfer function, and the differentiation of complex functions: advanced control-theoretic ideas helpful in the analysis presented in the body of the brief.

A Mathematical Perspective on Flight Dynamics and Control will give researchers and graduate students in aerospace control an alternative, mathematically rigorous means of approaching their subject.

About the Author:

The author is an assistant professor at the School of Aerospace and Mechanical Engineering of The University of Oklahoma and is presently teaching a graduate course in flight control. Dr. L’Afflitto holds a B.S., M.S., and Ph.D. degree in aerospace engineering and an M.S. degree in Mathematics and his research is currently focused on optimal control theory and differential games theory with applications to aerospace control problems, such as fuel-optimal path planning and formation flying.

 

To purchase or learn more about this book, please visit: http://www.springer.com/us/book/9783319474663

A group of students from Dr. Andrea L’afflitto’s Flight Controls class created the following video:

According to Dr. L’afflitto, this project consisted of designing an autopilot for a quadrotor using some modern, very aggressive control techniques. The purpose of this video is to show the results achieved graphically, however, the mathematical models, the control design problem and the numerical simulations have very deep roots.

“I am extremely proud of their work because these are all undergraduate students, but the quality and the mathematical complexity is the one of a graduate project,” said Dr. L’afflitto. “We all can imagine the impact of the development of such technology, considering the growing attention that OU is putting on the UAS technology.”

Video Transcript:

This video shows the result of a students’’ project developed as part of the AME 4513/5513 “Flight Controls” course at the University of Oklahoma in Fall 2016. A DJI F450 will inspect some buildings of OU’s main campus. The drone’s autopilot implements an algorithm based on Model Reference Adaptive Control.

An important feature of this simulation is that the quadrotor dynamics is not captured by a set of nonlinear differential equations, but it is deduced from a SimMechanics model of a DJI F450. This guarantees high accuracy of the results presented.

The adaptive control technology allows precise, aggressive maneuvers in the vicinity of obstacles, such as buildings.

[VIDEO]

Next, we compare the performance of a quadrotor (in white) implementing an adaptive control law and a quadrotor (in black) implementing a classic PID controller.

[VIDEO]

Created by: Blake Anderson

Riley Cotter

Jordan Logue

Kevin Murray Jr.

michael-zavlanos-dream-course

Dr. Michael Zavlanos visited AME on February 2, 2017 as part of Dr. Andrea L’Afflitto’s Dream Course, Modern Control Theory and Applications.

Abstract: Current robotic systems have the potential to accomplish a previously intractable scope of tasks. Their ever growing capabilities will soon allow them to operate autonomously outside the lab, in remote, unpredictable, and uncertain environments, where the presence of humans is dangerous or even impossible. For this to become possible, a fundamental challenge is to develop new methods that will enable teams of robotic sensors to collaboratively explore unknown environments and extract concise actionable information. In this talk,we present a novel approach to dynamically synthesize optimal controllers for a robotic sensor network tasked with estimating a collection of hidden states. The key idea is to divide the hidden states into clusters and then use dynamic programming to determine optimal trajectories around each hidden state as well as how far along the local optimal trajectories the robot should travel before transitioning to estimating the next hidden state within the cluster. Then, a distributed assignment algorithm is used to dynamically allocate controllers to the robot team from the set of optimal control policies at every cluster. Compared to relevant distributed state estimation methods, our approach scales very well to large teams of mobile robots and hidden vectors. We also present a distributed state estimation method that allows mobile sensor networks to estimate a set of hidden states up to a user-specified accuracy. This is done by formulating a LMI constrained optimization problem to minimize the worst case state uncertainty, which we solve in a distributed way using a new random approximate projections method that is robust to the state disagreement errors that exist among the robots as an Information Consensus Filter (ICF) fuses the collected measurements. To our knowledge, even though the distributed active sensing literature is well-developed, the ability to control worst-case estimation uncertainty in a distributed fashion is new. We present numerical simulations and experimental results that show the efficiency of the reposed methods.

Bio: Michael M. Zavlanos received the Diploma in mechanical engineering from the National Technical University of Athens (NTUA), Athens, Greece, in 2002, and the M.S.E. and Ph.D. degrees in electrical and systems engineering from the University of Pennsylvania, Philadelphia, PA, in 2005 and 2008, respectively. From 2008 to 2009 he was a Post-Doctoral Researcher in the Department of Electrical and Systems Engineering at the University of Pennsylvania, Philadelphia. He then joined the Stevens Institute of Technology, Hoboken, NJ, as an Assistant Professor of Mechanical Engineering, where he remained until 2012. Currently, he is an assistant professor of mechanical engineering and materials science at Duke University, Durham, NC. He also holds a secondary appointment in the department of electrical and computer engineering. His research interests include a wide range of topics in the emerging discipline of networked systems, with applications in robotic, sensor, and communication networks. He is particularly interested in hybrid solution techniques, on the interface of control theory, distributed optimization, estimation, and networking. Dr. Zavlanos is a recipient of the 2014 Office of Naval Research Young Investigator Program (YIP) Award, the 2011 National Science Foundation Faculty Early Career Development (CAREER) Award, as well as Best Student Paper Awards at GlobalSIP 2014 and CDC 2006.

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