Course Information
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Description (from WebSIS):
A learn-by-design introduction to modeling and control of discrete- and continuous-time systems, from intuition-building analytical techniques to more computational and data-centric strategies. Topics include: linear difference/differential equations (natural frequencies, transfer functions); controller metrics (stability, tracking, disturbance rejection); analytical techniques (PID, root-loci, lead-lag, phase margin); computational strategies (state-space, eigen-placement, LQR); and data-centric approaches (state estimation, regression, and identification). Concepts are introduced with lectures and online problems, and then mastered during weekly labs. In lab, students model, design, test, and explain systems and controllers involving sensors, actuators, and a microcontroller (e.g., optimizing thrust-driven positioners or stabilizing magnetic levitators). Students taking graduate version complete additional problems and labs.
Prerequisites:
We presume that 6.3100/2 students have taken some physics (atleast 8.01(GIR)) and a linear algebra class (18.C06 or 18.06). While not expected, students have reported benefitting 2.003, 16.002, 6.200, 6.300 and 18.03.
Labs
NEW FOR 2026: We are deemphasizing the postlab problem sets. Instead, we are adjusting the check-off interviews to help you achieve a deeper understanding. Also, we are adding a challenge lab (April 24), please expect to spend extra time on that lab.
The learn-by-design philosophy of 6.310 centers on weekly 3-hour labs. Two alternative lab sections are available:
- Fridays 10am-1pm in 38-545
- Fridays 2pm-5pm in 38-545
Most of the learning about design comes from working on the labs. Please work with a partner. It does not have to be the same partner for each week. Students who work in pairs (NOT triplets) typically get more out of the lab experience (and have more fun) than those who stoically work alone.
The weekly labs are organized as six projects that each comprise two of the 3-hour lab sessions. The first of these sessions focuses on constructing a system to be controlled, making measurements to characterize that system, and developing a preliminary design of a controller. The second session focuses on mastering the concepts presented in lecture and practiced in the prelab. Typically, you will derive models, use those models to design controllers, test those controllers, and then analyze test results.
The design labs are challenging, and are key learning experiences. The design labs are NOT exams! We expect you to need help (from peers and/or the staff), but we also expect you to succeed, and to be able to demonstrate a comprehensive understanding during checkoff interviews. The checkoff interviews are also NOT exams! They are intended to help you stretch your understanding and uncover gaps. They can be repeated during lab and/or during office hours with NO PENALTY.
Lectures
Two weekly lectures introduce the theory that is developed in the labs. NEW FOR 2026: Credit for answering lecture questions to encourage participation. One question per lecture, due at end of lecture, and half credit for incorrect answers.
PreLab Online Exercises
Online exercises provide an opportunity for you to develop an understanding of the theory that will be applied in the lab. These prelab exercises are delivered through this web site and you will receive immediate feedback about your progress. The questions are intended to help you test/verify your understanding, so incorrect answers can be resubmitted WITHOUT PENALTY. The prelab's goal is to help you develop the skills needed for the design lab, so please finish the prelab before starting the design lab.
YOU MUST COMPLETE 70% OF THE PRELAB BEFORE YOU CAN START THE SECOND HALF (PART B) OF EACH LAB!
Note: Most of our on-line questions can be answered by several of the AI systems. We trust that you are the best judge of how to learn using AI, and only ask that you respect our effort by being sure you are prepared for lab.
PostLab Problem Sets
We will post postlab problem sets that have more open-ended questions for some of the labs. They are intended to help deepen your understanding of the underlying theory, and we will provide solutions. However, for Spring 2026 we have decided to focus on enhancing the interview process, and will not be grading postlab problem sets.
Exams
There are neither quizzes nor a final exam in this subject.
Lab Hours
Staff will hold in-lab office hours at times posted on our home page, but may be adjusted based on class preferences. In addition, the fifth-floor lab itself is open until 11:45pm every day except Saturday.
Please take advantage of these times to finish labs and/or clarify your understanding of the course material. And PLEASE do not wait until the last minute to get help, as office hours can get very BUSY as due dates approach.
Grades on Labs and Prelabs
Your grades on the online questions and in-lab checkoffs are based on percentage completed, WITHOUT REGARD TO RETRIES!
Final Grade in Undergraduate Version (6.3100)
6.3100/2 is NOT competitively graded, grades are based on work completed. Since many tasks (prelabs and lab interviews) can be repeated without penalty, most students complete enough work to earn an A. For Spring 2026, we are trying to encourage regular lecture participation by including one graded question to be handed in at the end of each lecture (full credit for correct answers, half credit for incorrect). To keep this encouragement low-stress, you'll only need 50% of the total lecture‑question points, so sufficient participation could be: handing in always-correct answers at half the lectures; handing in always-incorrect answers at all the lectures; or handing in answers at two-thirds of the lectures that are correct only half the time.
To get an A you must
-- complete all of the checkoffs for all of the labs,
-- complete the challenge lab,
-- earn fifty percent of the lecture question points.
.
To get an B you must
-- complete all of the checkoffs in all of the labs,
-- complete the challenge lab OR earn fifty percent of the lecture question points.
To get an C you must
-- complete all of the checkoffs in at least 5 of the 6 labs.
To get an D you must
-- complete all of the checkoffs in at least 4 of the 6 labs.
Final Grade in Graduate Version (6.3102)
NOTE: For Spring 2026, 6.3102 students will be expected to complete an extra design lab.
To get an A you must
-- satisfy all of the criteria for an A in 6.3100 and
-- use a state-space controller to complete the challenge lab.
To get an B you must
-- satisfy all of the criteria for a B in 6.3100 and
-- complete the challenge lab.
Extension Policy
Our goal is to help you to get the most out of your educational experience in this subject and beyond. As with most subjects at MIT, this subject is fast-paced and challenging, though we try to minimize stress with our penalty-free retry policies (you never fail, you just haven't succeeded yet). Nevertheless, since we insist that you eventually demonstrate thorough understanding in each of more than thirty staff interviews, it can be difficult to catch up if you fall too far behind.
If you find yourself having difficulties or find yourself falling behind, please do not struggle alone. Discuss the situation with the staff, with your academic advisor, and/or S^3.
We will do all that we can to provide accomodations if unplanned issues (such as illness or personal problems) arise. Please consult an instructor if you have concerns.
Collaboration and AI Policy
The on-line prelab questions are intended to prepare you for the lab, the lab interviews give us an opportunity to "debug" your understanding, and postlab problem sets are intended to deepen your understanding. In our experience, students who work through prelabs, labs, and postlabs with a partner (or a sequence of partners) are more efficient and learn more. They spend far less time tripping over minor mistakes, and it is hard to overstate the pedagogical value of explaining one's thinking to a partner.
To encourage partnering, our only collaboration policy is that during lab interviews, we will do our best to ensure that both students understand the material.
