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NPTEL

Advanced Process Control

NPTEL and Indian Institute of Technology Bombay via YouTube

Overview

Instructor: Prof. Sachin Patwardhan, Department of Chemical Engineering, IIT Bombay.

This course has been designed to introduce concepts of multivariable state feedback controller synthesis using discrete time state space models. Development of control relevant dynamic models is viewed as an integral part of the process of controller synthesis. Thus, the course begins with the development of continuous time and discrete time linear perturbation models (state space and transfer functions) starting from mechanistic models commonly used in engineering. However, in practice, a mechanistic dynamic model may not be available for a system. In such a situation, control relevant discrete dynamic black-box models can be developed using perturbation test data. Development of output error, ARX and ARMAX models from time series data and constructing state realizations of the identified models is dealt next.

Syllabus

Introduction and Motivation.
Linearization of Mechanistic Models.
Linearization of Mechanistic Models (Contd.).
Introduction to z-transforms and Development of Grey-box models.
Introduction to Stability Analysis and Development of Output Error Models.
Introduction to Stochastic Processes.
Introduction to Stochastic Processes (Contd.).
Development of ARX models.
Statistical Properties of ARX models and Development of ARMAX models.
Development of ARMAX models (contd.) and Issues in Model Development.
Model Structure Selection and Issues in Model Development (contd.).
Issues in Model Development (contd.) and State Realizations of Transfer Function Models.
Stability Analysis of Discrete Time Systems.
Lyapunov Functions and Interaction Analysis and Multi-loop Control.
Interaction Analysis and Multi-loop Control (contd.).
Multivariable Decoupling Control and Soft Sensing and State Estimation.
Development of Luenberger Observer.
Development of Luenberger Observer (contd.) and Introduction to Kalman Filtering.
Kalman Filtering.
Kalman Filtering (contd.).
Kalman Filtering (contd.).
Pole Placement State Feedback Control Design and Introduction to Linear Quadratic Gaussian Control.
Linear Quadratic Gaussian (LQG) Regulator Design.
Linear Quadratic Gaussian (LQG) Controller Design.
Model Predictive Control (MPC).
Model Predictive Control (contd.).

Taught by

nptelhrd

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Reviews

3.6 rating, based on 5 Class Central reviews

Start your review of Advanced Process Control

  • S Suhail Basha
    Good understanding by this videos and these helps me to aquire more and more knowledge easily from this videos we will look forward for more courses that can be easily understandable by the videos
  • Profile image for Meenakshi Nair
    Meenakshi Nair
    Very informative and has good quality lectures.. excellent study material and videos are very well irganized .. gave a lot of insight to things that we had no idea of
  • Profile image for Talha Siddiqui
    Talha Siddiqui
    Great Lectures series that I've seen , great course advanced process control. o got to learn alot many things Interesting. Process control is the study and application of automatic control in the field of chemical engineering. The primary objective…
  • MR. KISHAN
    Good teaching and solving doubts .great learning.Easy to understand.On time course completion ..
    Good teaching and solving doubts .great learning.Easy to understand.On time course completion ..
  • Thennarasu.E
    This course is very useful for the all students iam so happy in to the the class is excellent ok coheing

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