Unit 1 Process Modeling

4 lecture hours

• State-space model: General form and canonical form
• Input/output model: transfer function and coprime polynomials
• Plant Parametric model: Linear and bilinear parametric models

Unit 2 Introduction to process identification

4 lecture hours

• Frequency domain expression
• Program Name: Engineering Level: PG Branch: Applied Instrumentation Course / Subject Code : ME01067041 Course / Subject Name : Process Modeling and Identification w.e.f. 2024-25 http://syllabus.gtu.ac.in/ Page no. 1 of 2 signal spectra
• model structure
• least square method
• procedure steps for process identification

Unit 3 Identification of LTI process

8 lecture hours

• sets of linear models
• transfer function models
• state-space models
• distributed parameter models
• model structures and identifiability

Unit 4 Identification of Time varying and nonlinear systems

8 lecture hours

• linear time- varying models
• models with nonlinearities
• nonlinear state space models
• Black box models

Unit 5 Nonparametric time and frequency domain methods

8 lecture hours

• transient response and correlation analysis
• frequency response analysis
• Fourier analysis
• spectral analysis

Unit 6 Parametric estimation methods

• Minimizing prediction errors
• Linear regressions
• least squares method
• maximum Likelihood method 6 10%

Unit 7 Convergence and consistency

• Conditions on the data set, Prediction- error approach
• consistency and identifiability
• correlation approach 4 10%