IC 1002 ADAPTIVE CONTROL 3 0 0 100
AIM
To gain knowledge on adaptive control of systems through parameter identification and
controller retuning.
OBJECTIVES
i. To study the definition of adaptive control and methods of adaptation.
ii. To study the parameter identification of systems.
iii. To study the self-tuning of PID controllers based on parameter identification.
iv. To study the model reference adaptive control.
v. To study the practical application through case studies.
1. INTRODUCTION 9
Introduction to adaptive control - Effects of process variations –
Adaptive control schemes – Adaptive control problem – Non-parametric identification – Step response method – Impulse response method – Frequency response method.
2. PARAMETRIC IDENTIFICATION 9
Linear in parameter models - ARX – ARMAX – ARIMAX – Least square estimation – Recursive least square estimation – Extended least square estimation – Maximum likelihood estimation – Introduction to non-linear systems identification - Pseudo random binary sequence.
3. SELF-TUNING REGULATOR 9
Deterministic in-direct self-tuning regulators – Deterministic direct self-tuning regulators – Introduction to stochastic self-tuning regulators – Stochastic indirect self-tuning regulator.
4. MODEL REFERENCE ADAPTIVE CONTROLLER 9
The MIT rule – Lyapunov theory – Design of model reference adaptive controller using MIT rule and Lyapunov theory – Relation between model reference adaptive controller and self-tuning regulator.
5. TUNING OF CONTROLLERS AND CASE STUDIES 9
Design of gain scheduling controller - Auto-tuning of PID regulator – Stability analysis of adaptive controllers – Application of adaptive control in chemical reactor, distillation column and variable area tank system.
L = 45 Total = 45
TEXT BOOK
1. Karl J. Astrom & Bjorn Wittenmark, ‘Adaptive Control’, Pearson Education (Singapore), Second Edition, 2003.
REFERENCE BOOKS
1. T. C.H.A. Hsia, ‘System Identification’, Lexington books, 1974.
2. Stephanopoulis G. ‘Chemical Process Control’, Prentice Hall of India, New Delhi, 1990.
AIM
To gain knowledge on adaptive control of systems through parameter identification and
controller retuning.
OBJECTIVES
i. To study the definition of adaptive control and methods of adaptation.
ii. To study the parameter identification of systems.
iii. To study the self-tuning of PID controllers based on parameter identification.
iv. To study the model reference adaptive control.
v. To study the practical application through case studies.
1. INTRODUCTION 9
Introduction to adaptive control - Effects of process variations –
Adaptive control schemes – Adaptive control problem – Non-parametric identification – Step response method – Impulse response method – Frequency response method.
2. PARAMETRIC IDENTIFICATION 9
Linear in parameter models - ARX – ARMAX – ARIMAX – Least square estimation – Recursive least square estimation – Extended least square estimation – Maximum likelihood estimation – Introduction to non-linear systems identification - Pseudo random binary sequence.
3. SELF-TUNING REGULATOR 9
Deterministic in-direct self-tuning regulators – Deterministic direct self-tuning regulators – Introduction to stochastic self-tuning regulators – Stochastic indirect self-tuning regulator.
4. MODEL REFERENCE ADAPTIVE CONTROLLER 9
The MIT rule – Lyapunov theory – Design of model reference adaptive controller using MIT rule and Lyapunov theory – Relation between model reference adaptive controller and self-tuning regulator.
5. TUNING OF CONTROLLERS AND CASE STUDIES 9
Design of gain scheduling controller - Auto-tuning of PID regulator – Stability analysis of adaptive controllers – Application of adaptive control in chemical reactor, distillation column and variable area tank system.
L = 45 Total = 45
TEXT BOOK
1. Karl J. Astrom & Bjorn Wittenmark, ‘Adaptive Control’, Pearson Education (Singapore), Second Edition, 2003.
REFERENCE BOOKS
1. T. C.H.A. Hsia, ‘System Identification’, Lexington books, 1974.
2. Stephanopoulis G. ‘Chemical Process Control’, Prentice Hall of India, New Delhi, 1990.
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