EEE

# CIC333: System Identification syllabus for EEE 2021 regulation (Professional Elective-V)

System Identification detailed syllabus for Electrical & Electronics Engineering (EEE) for 2021 regulation curriculum has been taken from the Anna Universities official website and presented for the EEE students. For course code, course name, number of credits for a course and other scheme related information, do visit full semester subjects post given below.

For Electrical & Electronics Engineering 6th Sem scheme and its subjects, do visit EEE 6th Sem 2021 regulation scheme. For Professional Elective-V scheme and its subjects refer to EEE Professional Elective-V syllabus scheme. The detailed syllabus of system identification is as follows.

System Identification

#### Unit I

NON PARAMETRIC METHODS 9 Nonparametric methods: Transient analysis – frequency analysis – Correlation analysis -Spectral analysis.

#### Unit III

RECURSIVE IDENTIFICATION METHODS 9 The recursive least squares method – Recursive Instrumental variable method-the recursive prediction error method-model validation and model structure determination. Identification of systems operating in closed loop: Identifiability considerations – Direct identification – Indirect identification – Joint input – Output identification.

#### Unit V

NONLINEAR SYSTEM IDENTIFICATION 9 Modeling of nonlinear systems using ANN- NARX & NARMAX – Training Feed-forward and Recurrent Neural Networks – TSK model – Adaptive Neuro-Fuzzy Inference System (ANFIS) -Introduction to Support Vector Regression.

#### Course Outcomes:

1. Ability to design and implement state estimation schemes. L5
2. Ability to develop various models (Linear & Nonlinear) from the experimental data. L5
3. Be able to choose a suitable model and parameter estimation algorithm for the identification of systems. L3
4. Be able to illustrate verification and validation of identified model. L3
5. Ability to develop the model for prediction and simulation purposes using suitable control schemes. L5

#### Text Books:

1. Lennart Ljung, System Identification: Theory for the user, 2nd Edition, Prentice Hall, 1999.
2. Dan Simon, Optimal State Estimation Kalman, H-infinity and Non-linear Approaches, John Wiley and Sons, 2006,
3. Tangirala, A.K., Principles of System Identification: Theory and Practice, CRC Press, 2014, 1st Edition.