Faculty of Engineering and Material Sciences (EMS)
Courses Offered
Classical Control
5th Semester
The Classical Control course covers the fundamentals of control theory, mathematical description of linear systems, stability and instability of linear systems and various techniques to analyze and design closed loop control systems to ensure desired performance and stability.
Mechatronics Engineering
6th Semester
The Mechatronics Engineering course explores the integration of mechanical and electrical components with practical applications of control theory through microcontroller-based systems. It provides a foundation for embedded systems and their real-world implementations.
Advanced Mechatronics Engineering
9th Semester
Building on the Mechatronics Engineering course, this advanced course delves into non-linear control of non-linear systems and advanced embedded systems.
Reinforcement Learning
10th Semester
This course covers core concepts of reinforcement learning, including Markov Decision Processes (MDPs), Bellman's equation, and advanced techniques like Deep Neural Networks and actor-critic methods. It also explores Optimal Control strategies, such as Model Predictive Control (MPC), for efficient and effective control system design.