EE2029 SYSTEM IDENTIFICATION AND ADAPTIVE CONTROL
UNIT I PARAMETRIC METHODS 5
Nonparametric methods: Transient analysis-frequency analysis-Correlation analysis-
Spectral analysis.
UNIT II PARAMETRIC METHODS 10
Linar Regression: The Lease square esimate-best liner unbiased etimation under
linear constraints- updating the Parameter estimates for linear regression models-
Predcion error methods: Description of Prediction error methods-Optimal Predictio –
relationships between Prediction error methods and other identification methodstheoretical
analysis.
Instrumental variable methods: description of nstrumental variable methods-theoretical
analysis-covariance matrix of IV estimates- Comparison of optimal IV predicion error
methods.
UNIT III RECURSIVE IDENTIFICATION METHODS 10
The recursive lest squares method-the recursive Instrumentl varible method-the
recursive prediction error method-model validatio and model structure etermination.
Indenification of systems operating in closed loop: Identifiability considerations-direct
indentification-Indirect indentification-joint input – output identification.
UNIT IV ADAPTIVE CONTROL SCHEMES 10
Introduction – users- Definitions-auto tuning-types of adaptive control-gain scheduling
controller-model reference adaptive control schemes – self tunning controller. MRAC
and STC : Approaches – The Gradient approach – Lyapunov functions – Passivity
theory – pole placement method Minimum variance control – Predictive control.
UNIT V ISSUES IN ADAPIVE CONTROL AND APPLICATION 10
Stability – Convergence – Robustness – Application of adaptive conrol.
TOTAL : 45 PERIODS
TEXT BOOKS
1. Soderstorm.T and Petre stioca, System Identification, Prentice Hall International
(UK) Ltd. 1989.
2. Karl J.Astrom and Bjorn Wittenmark, Adaptive Conrol, Pearson Education, 2nd
Editon, 2001.
REFERENCES
1. Ljung,L.System Identification: Theory for the user, Pretice Hall, Englewood cliffs, 1987.
2. Sastry S. and Bodson M., daptive control – stability, Convergence ad Robustness,
Prentice Hall inc., New Jersey, 12989.
UNIT I PARAMETRIC METHODS 5
Nonparametric methods: Transient analysis-frequency analysis-Correlation analysis-
Spectral analysis.
UNIT II PARAMETRIC METHODS 10
Linar Regression: The Lease square esimate-best liner unbiased etimation under
linear constraints- updating the Parameter estimates for linear regression models-
Predcion error methods: Description of Prediction error methods-Optimal Predictio –
relationships between Prediction error methods and other identification methodstheoretical
analysis.
Instrumental variable methods: description of nstrumental variable methods-theoretical
analysis-covariance matrix of IV estimates- Comparison of optimal IV predicion error
methods.
UNIT III RECURSIVE IDENTIFICATION METHODS 10
The recursive lest squares method-the recursive Instrumentl varible method-the
recursive prediction error method-model validatio and model structure etermination.
Indenification of systems operating in closed loop: Identifiability considerations-direct
indentification-Indirect indentification-joint input – output identification.
UNIT IV ADAPTIVE CONTROL SCHEMES 10
Introduction – users- Definitions-auto tuning-types of adaptive control-gain scheduling
controller-model reference adaptive control schemes – self tunning controller. MRAC
and STC : Approaches – The Gradient approach – Lyapunov functions – Passivity
theory – pole placement method Minimum variance control – Predictive control.
UNIT V ISSUES IN ADAPIVE CONTROL AND APPLICATION 10
Stability – Convergence – Robustness – Application of adaptive conrol.
TOTAL : 45 PERIODS
TEXT BOOKS
1. Soderstorm.T and Petre stioca, System Identification, Prentice Hall International
(UK) Ltd. 1989.
2. Karl J.Astrom and Bjorn Wittenmark, Adaptive Conrol, Pearson Education, 2nd
Editon, 2001.
REFERENCES
1. Ljung,L.System Identification: Theory for the user, Pretice Hall, Englewood cliffs, 1987.
2. Sastry S. and Bodson M., daptive control – stability, Convergence ad Robustness,
Prentice Hall inc., New Jersey, 12989.
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