Nonlinear & Adaptive Control Course | IIT Delhi | Prof. Shubhendu Bhasin
Course Details
| Exam Registration | 73 |
|---|---|
| Course Status | Ongoing |
| Course Type | Elective |
| Language | English |
| Duration | 4 weeks |
| Categories | Electrical, Electronics and Communications Engineering |
| Credit Points | 1 |
| Level | Postgraduate |
| Start Date | 19 Jan 2026 |
| End Date | 13 Feb 2026 |
| Enrollment Ends | 02 Feb 2026 |
| Exam Registration Ends | 16 Feb 2026 |
| Exam Date | 29 Mar 2026 IST |
| NCrF Level | 4.5 — 8.0 |
Master Advanced Control Systems: A Deep Dive into Nonlinear and Adaptive Control
In the evolving landscape of modern engineering, from autonomous drones to sophisticated robotic manipulators, the ability to design controllers for complex, uncertain systems is paramount. The Nonlinear and Adaptive Control course, offered by the prestigious Indian Institute of Technology Delhi (IIT Delhi), provides a rigorous foundation in these critical advanced control methodologies. Designed for postgraduate students and professionals, this 4-week intensive program is led by Prof. Shubhendu Bhasin, an expert from the Department of Electrical Engineering.
Meet Your Instructor: Prof. Shubhendu Bhasin
Prof. Shubhendu Bhasin is an Associate Professor in the Control and Automation Group within IIT Delhi's Department of Electrical Engineering. His academic journey includes an MS and PhD from the University of Florida, Gainesville, where he was part of the renowned Nonlinear Controls and Robotics Lab. His research portfolio spans Nonlinear and Adaptive Control, Robotics, Autonomous Systems, Reinforcement Learning Control, and Approximate Dynamic Programming. This blend of theoretical depth and practical application experience makes him the ideal guide for this advanced subject.
Course Overview and Objectives
This is an advanced course focused on systematic control design for systems with parametric uncertainty. Moving beyond linear control theory, it equips participants with tools to handle real-world systems where dynamics are nonlinear and parameters are unknown or varying.
PREREQUISITES: A solid understanding of Lyapunov Stability Theory and a working knowledge of MATLAB/Simulink are essential. The course builds directly on foundational knowledge from introductory courses in Nonlinear Systems or Nonlinear Control.
Detailed 4-Week Course Layout
The course is meticulously structured over four weeks to build competence from the ground up:
- Week 1: Introduction to Adaptive Control - Foundational concepts, problem formulation, and the need for adaptive schemes in control engineering.
- Week 2: Model Reference Adaptive Control (MRAC) - In-depth study of MRAC architecture, design procedures, and stability analysis for systems to track the behavior of a reference model.
- Week 3: Robust Adaptive Control – 1 - Addressing real-world challenges like disturbances and unmodeled dynamics. Introduction to robustness modifications and techniques.
- Week 4: Robust Adaptive Control – 2 - Advanced robustification methods, ensuring adaptive control systems remain stable and perform reliably in non-ideal environments.
Essential Reference Books
The course curriculum is supported by seminal texts in the field, providing students with comprehensive resources for deeper study:
| Book Title | Authors | Link/Details |
|---|---|---|
| Adaptive Control Tutorial | P. Ioannou and B. Fidan | SIAM, 2006 |
| Stable Adaptive Systems | K. S. Narendra and A. M. Annaswamy | Prentice-Hall, 1989 |
| Adaptive Control | S. Sastry and M. Bodson | Prentice-Hall, 1989 (Available Online) |
| Nonlinear Systems | H. K. Khalil | Prentice Hall, 3rd Edition, 2002 |
| Applied Nonlinear Control | J.J.E. Slotine and W. Li | Prentice-Hall, 1991 |
Who Should Enroll?
This course is ideally suited for:
- Postgraduate students (M.Tech, M.S., Ph.D.) in Electrical, Electronics, and Communications Engineering, Mechanical Engineering (with controls focus), and Aerospace Engineering.
- Research scholars and academics working in control theory, robotics, or autonomous systems.
- Industry professionals in R&D roles within automotive, aerospace, robotics, and automation sectors seeking to advance their theoretical knowledge in adaptive systems.
By the end of this course, participants will have developed a strong conceptual and methodological framework for designing adaptive controllers, a skill set highly valued in cutting-edge research and development in automation and intelligent systems. Under the guidance of Prof. Bhasin, students will navigate from fundamental principles to the forefront of robust adaptive control techniques.
Enroll Now →