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Advanced Process Control. Instructor: Prof. Sachin Patwardhan, Department of Chemical Engineering, IIT Bombay.
722 years, 1 month
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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 integral part of the process of controller synthesis. Thus, the course begins with 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. (from nptel.ac.in)
Course Currilcum
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- Lecture 01 – Introduction and Motivation Unlimited
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- Lecture 02 – Linearization of Mechanistic Models Unlimited
- Lecture 03 – Linearization of Mechanistic Models (cont.) Unlimited
- Lecture 04 – Introduction to z-Transforms and Development of Grey-box Models Unlimited
- Lecture 05 – Introduction to Stability Analysis and Development of Output Error Models Unlimited
- Lecture 06 – Introduction to Stochastic Processes Unlimited
- Lecture 07 – Introduction to Stochastic Processes (cont.) Unlimited
- Lecture 08 – Development of ARX Models Unlimited
- Lecture 09 – Statistical Properties of ARX Models and Development of ARMAX Models Unlimited
- Lecture 10 – Development of ARMAX Models (cont.), Issues in Model Development Unlimited
- Lecture 11 – Model Structure Selection and Issues in Model Development Unlimited
- Lecture 12 – Issues in Model Development and State Realizations of Transfer Function Models Unlimited
- Lecture 17 – Development of Luenberger Observer Unlimited
- Lecture 18 – Development of Luenberger Observer (cont.), Introduction to Kalman Filtering Unlimited
- Lecture 19 – Kalman Filtering Unlimited
- Lecture 20 – Kalman Filtering (cont.) Unlimited
- Lecture 21 – Kalman Filtering (cont.) Unlimited
