PLEASE COME TO ANY ADVISING SESSION WITH A COMPLETED PLAN OF STUDY. YOU CAN ALWAYS CHANGE IT AFTER YOUR SESSION. While you can revise your plan each semester, you should always have a valid plan in hand that gets you a degree in your desired amount of time.
- Please use the on-line Course Planning Form
- You are not required to have your PLAN OF STUDY signed by an advisor, though it is a good idea to do this.
- Whether your plan is signed or not, once you have it finalized, email a copy to the appropriate grad coordinator and to Prof. Grizzle. When you revise it, re-send it.
Kevin Calhoun, MS Grad Coordinator, email@example.com, 3405 EECS, 764-3344
Jose-Antonio Rubio, PhD Grad Coordinator, firstname.lastname@example.org, 3404 EECS, 764-9387
Most students should take 3 courses in the Fall term. This may seem like very little, and the first two or three weeks of the term, it may seem like a light load, but after that, you will be BUSY.
- EECS 560 is a prerequisite for essentially all of the control classes that you may wish to take in the Winter term. Hence, if you have not already had a linear-algebra-based linear systems course, then you really need to take EECS 560 in the Fall term.
- Almost all of your remaining choices are flexible.
- If you are planning to take the PhD qualifying exam, then you should probably take EECS 501. It is not required, but the majority of control PhD students find the material to be very useful. Also, taking a math course, such as Math 451, is not a bad idea.
- If you are not planning to take the PhD qualifying exams, then EECS 501 may be right for you, and it may not be right for you. It is a personal choice and Prof. Grizzle does not really know how to make that choice for you. Did you like probability as an undergrad? If not, then why torture yourself with EECS 501?
- What should you plan to take in the Winter term? EECS 565 is very highly recommended for ALL STUDENTS. EECS 562 is highly recommended for all PhD students; most masters students will like the course as well.
- If you are a masters student and have not taken an embedded control course, then you should think about EECS 461. Embedded controls seems to be very hot with recruiters the past several years. If you are a PhD student and hope to do applied research, you may like EECS 461 as well. If you prefer theory, well, then maybe skip EECS 461.
- We have a lot of control courses! If they were not valuable for a subset of students, we would not offer them. I am confident you will find something that interests you.
- Regarding minors: You do **not** have to minor in a traditional subject, such as signal processing or communications. You can design a collection of courses that makes sense and call it a minor. For example, even though we do not have an official robotics minor in EE:S, you can create your own minor in that subject. You could take a collection of courses in automotive systems and call it a minor. The same applies to power systems and almost any other technical subject you can imagine. The courses just have to make sense. The courses do not have to be EECS courses. **You have a lot of flexibility.** How do you know if a collection of courses makes sense? Well, could you explain it to a recruiter and have him or her believe you?
- Control Courses in the College of Engineering,
New Robotics PhD Program in College of Engineering,
Robotics and Related Courses, and Previous Robotics MS Program in the College of Engineering [Is being replaced by the newer program]
Q & A
- Q: Can some ME courses be taken for EECS credit? A: Yes! The key thing is that the course must have a heavy EE content. An example is ME 552 Mechatronics. It is already approved for EECS credit. There is an ME course on Batteries and another on Hybrid Electric Vehicles. You can check with the Graduate Systems Staff to see if they are already approved for EECS credit. Otherwise, you may have to file a petition, which is rather easy to do, by the way.
- Q: Does the Interpro course ``Energy Systems'', ESENG 501, count for Rackham credit? A: Yes, provided you register for the course under ``Rackham'' and earn a letter grade of B- or higher. Pass Fail (S, U) is not acceptable for grad credit in the Systems Grad Program.
- Q: If I really like the hardware side of control, what are the best courses? A: EECS 461 (Embedded Control) is an excellent choice. An alternative is EECS 452 ( Digital Signal Processing Design Laboratory), which emphasizes DSP microprocessors; this course also has a project. Continuing in the vein of microprocessors, Professors Brehob and Dick often teach courses on embedded processors from a computer engineering point of view; it is worth checking to see what they are teaching. Moving away from microprocessors and looking at hardware on the system level, ME 552 (Electromechanical System Design) would be a great choice. Still another way to get exposure to hardware is through robotics. Specifically, EECS 498 (Autonomous Robotics Laboratory) and EECS 568 (Mobile Robotics: Methods and Algorithms).
- We are in a state of flux with the new MS/PhD program that combines EE: Systems and EE into a single degree program. The advice below is for the EE:Systems program.
- Make your major either Control or Signal Processing. If your major is Control, continue reading here. Else, exit, and see an advisor for Signal Processing.
- Some links were given above for where to find robotics courses. I will highlight here a few specific courses
- EECS 498 Hands-On Robotics
- ME 552 Mechatronic Systems Design (Also approved for EECS Credit)
- ME/EECS 567 Introduction to Robotics
- NA568/EECS568: Mobile Robotics: Methods & Algorithms
- ROB 550 Robotic Systems Laboratory
- Computer Vision, Machine Learning, Dynamics (ME 453, ME 540) are also good!
- ME 458 Automotive Engineering
- ME 542 Vehicle Dynamics
- ME 566 Modeling, Analysis, and Control of Hybrid Electric Vehicles
- ME 568 Vehicle Control Systems
- ME 569 Control of Advanced Powertrain Systems
- Take a course in computer vision, a key sensor for such systems
- Take EECS 564: Estimation, Filtering, and Detection.,
- Take a course in mobile robotics, such as EECS568, because the subsystems involved are similar.
- Take the Vehicle Dynamics course, ME 542.
- Take nonlinear control
- Look for special topics courses on the subject, primarily in ME
- EECS 566 may be helpful.
- Other areas: AI, Machine Learning, Hybrid Systems.