Information

Course Description

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 the graduate version complete additional problems and labs.

Prerequisites: Physics II (GIR) and 18.06 or permission of instructor

Course Structure

This subject covers a curated list of topics in dynamical system modeling and control, in both continuous and discrete time. It is design-oriented, so a majority of the learning comes from working on the labs, preferably with a partner.

Each lab spans two weeks and comprises three segments:

• A prelab reviews the conceptual basis of the lab (which was introduced in the lectures) and tests your understanding with online questions. If you answer a prelab question incorrectly, you can resubmit WITHOUT PENALTY. The goal is to make sure that you are ready to do the lab, so the prelab questions must be answered before you start your lab session.
• The labs are designed to be the primary learning experience, and you are welcome to get help from peers and/or the staff. We strongly recommend that you work with a partner. After you have completed each milestone, you will be asked to demonstrate your understanding by completing a checkoff with the staff. Checkoffs can be done individually or in pairs, except for the final check-off, which must be done individually. Checkoffs can be repeated (even multiple times) with NO PENALTY. All checkoffs should be completed before the Tuesday that follows each two-week lab.
• A postlab asks you to reflect on the lab by answering follow-up questions and extensions to each lab. Postlabs are written assignments, and you can submit your answers by uploading common image files (such as jpg or png) or pdf files via the upload links on each postlab assignment. Postlabs should be submitted by the dates given on each assignment.

Office Hours

Office hours will be available at times posted on our home page. Please take advantage of these times to finish labs and/or clarify your understanding of the course material.

Do not wait until the last minute to get help, as office hours can get very BUSY as due dates approach.

Grading and late policy

Your grade on the online questions and in-lab checkoffs will be based on completion. Your written postlab questions will be graded as check (good understanding), check+ (great understanding), or check- (conceptual gaps). You can earn an A in this subject by completing all of the lab checkoffs, completing at least 90% of the online questions, and receiving an average of "check" on the postlab questions.

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 (but hopefully not stressful) by design. If you have difficulties or find yourself falling behind, please 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.