Course12710153027 lectures
Intelligent Feedback and Control
Prof. Leena Vachhani · IIT Bombay
About
In practice, achieving 100% control objective is not the aim and allows bandwidth to achieve multiple objectives using well-known PID controller design. However, it is important to understand where is the possibility of satisfying control objectives using PID control. The course connects modern control techniques with the classical PID control approach wherever possible. This approach recognizes the strength of PID control design and suggests that it should be the preferred choice when the control objectives are not overly stringent. The systematic approach of learning applicability and limitations of PID control and their advanced variants through this course makes it beneficial for the students/professionals developing controllers for practical applications.
Intended audience: Community interested in learning advanced control design concepts with strong basis in practical problems.
Prerequisites: Control engineering topics covering transfer function, state-space model and stability
Lectures
Week 1
- Lecture 1 : Understanding PID Control
- Lecture 2 : Process Model: Experimental Methods
- Lecture 3 : Model Reduction
- Lecture 4 : Disturbance Models and PID
- Lecture 5 : PID Tuning Methods
- Lecture 6 : PID Tuning Methods (contd.)
Week 2
- Lecture 7 : Selection of PID Controller
- Lecture 8 : Designing Controllers in a Jugaad Way
- Lecture 9 : To explain why jugaad works....
- Lecture 10 : Feedforward Design
- Lecture 11 : State-space methods - Feedforward Control
- Lecture 12 : Internal Model Control (IMC)
Week 3
- Lecture 13 : Overview of Control Techniques
- Lecture 14 : Multivariable Control
- Lecture 15 : Multivariable Control (contd.)
- Lecture 16 : Decoupler Design
- Lecture 17 : Feedback Decouplers and Centralized Controllers
- Lecture 18 : Large Scale MIMO Systems
- Lecture 19 : Understanding irreducible transfer functions
Week 4
- Lecture 20 : Data Driven PID Control
- Lecture 21 : Data Driven PID Control (contd.)
- Lecture 22 : Control and Learning
- Lecture 23 : Control using Reinforcement Learning (RL)
- Lecture 24 : Reinforcement learning based control for inverted pendulum
- Lecture 25 : Policy Gradient based Reinforcement Learning
- Lecture 26 : Using MATLAB for Reinforcement Learning
- Lecture 27 : Course Summary
Syllabus and materials
At NPTEL, as the course publishes them.
Credits and licence
- Institution
- IIT Bombay
- Department
- Multidisciplinary
- Teacher
- Prof. Leena Vachhani
- Level
- Undergraduate
- Language
- English
- Source
- NPTEL
- Licence
- CC BY-NC-SA, as NPTEL states it. Non-commercial use only. NPTEL's terms
- Attribution
- NPTEL states: "Distributed under Creative Commons Attribution-ShareAlike / CC BY - NC - SA", beside a BY-NC-SA badge.
- Who can watch
- NPTEL gives no rating. Invisible Network shows it to Teens profiles and older, judged from what the source says about it. How courses are placed