EE650, Basics of Modern Control Systems, 2026-2027, Sem I
This is a course webpage for Basics of Modern Control Systems, 2026-2027, Sem I
Objective of the course:
The objective of this course is to provide a rigorous introduction to modern control theory using state-space methods for system modeling, analysis, estimation, and controller design. It bridges the gap between classical control techniques and contemporary control methodologies used in research and advanced engineering applications.
Outcomes of the course:
At the end of the course, students will be able to model and analyze linear and nonlinear dynamical systems using state-space methods, and evaluate system properties such as controllability, observability, and stability. They will be able to design modern controllers and state estimators, implement them using computational tools, and apply appropriate control techniques to solve practical engineering problems
Instructor
Abhilash Patel, apatel[at]iitk.ac.in
Teaching Assistants
Schedule
Wednesdays and Fridays, 18:15–19:30, at L10
Announcements
Important course-related updates will be posted here with the latest announcement appearing at the top. Please check this page regularly in addition to your IITK email.
- [30-July-2026] Welcome to EE650! Course webpage is now active. Please download the First Course Handout (FCH) and read it before the next class.
- [31-July-2026] Project Guidelines uploaded. Click
| here. |
- [14-Aug-2026] Assigment 1 uploaded. Download from
| here. |
Lectures
| Lecture |
Topics |
Class Discussion |
Handout |
Reading Recommended |
| L1/30-07-2026 |
Course Mechanics and motivation |
FCH
|
|
|
| L2/07-08-2026 |
Revisit to Linear Algebra |
L2
|
Note 1
|
MG 2.1-2.4 |
| L3/12-08-2026 |
State-space modeling |
L3
|
Note 2
|
MG 3.2-3.5 |
| L4/14-08-2026 |
Equilibrium, Linearization, Discrete-form; Project Discussion |
L4
|
Note 2
|
MG 3.2-3.5 |
| L5/19-08-2026 |
Data-driven modeling or Machine Learning, Parametric Models: AR, ARX, ARMAX, NARMAX, LIP |
L5
|
Note 3
|
|
| Coming Next ↓ |
| L6/xx-08-2026 |
Models: NN, PINN, Learning: Least Square, Recurisve Least Square, Gradient-descent |
|
Note 3
|
|
| L7/xx-08-2026 |
Learning Non-parametric Models: DMD, Koopman |
|
Note 3
|
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Recommended Textbooks
- [Og] K. Ogata, Modern Control Engineering, 5th ed. Pearson, 2010
- [NG] M Gopal, Modern Control System Theory, New Age International Publishers, 1993
- [DB] H K Khalil, Nonlinear Systems, 3rd Edition, Pearson, 2001.
MATLAB Codes for Simulation
- Simulation of Bouncing Ball, modelled as Hybrid System bouncing_ball.m
- Simulation of Pendulum, a classical example of nonlinear system pendulum.m
Additional Readings