EECE 574 - Adaptive Control - Basics of System Identification

More documents

Recommendations

Info

Models for Identification Models for Identification A few words of caution: Do NOT fall in love with your model... When map disagrees with Nature, TRUST Nature Swedish Army Manual Guy Dumont (UBC) EECE574 - Basics of System Identification 6 / 40
Models for Identification Models for Identification The Impulse Response Model One of the simplest: y(k) = ∞ hju(k − j − 1) j=0 hj is the j th element of the impulse response of the process. Assuming that the impulse response asymptotically goes to zero, it may be truncated after the nh th element: nh y(k) = hju(k − j − 1) j=0 This is called a Finite Impulse Response (FIR) model and can only be used for stable processes. Used mainly in adaptive filtering. Guy Dumont (UBC) EECE574 - Basics of System Identification 7 / 40
Page 1 and 2: EECE 574 - Adaptive Control Basics
Page 3 and 4: Introduction System Identification
Page 5: Models for Identification Models fo
Page 9 and 10: Models for Identification Models fo
Page 15 and 16: Least-Squares Identification Least-
Page 21 and 22: Least-Squares Identification Proper
Page 23 and 24: Least-Squares Identification Proper
Page 25 and 26: Alternatives to Least-Squares Gener
Page 27 and 28: Alternatives to Least-Squares Gener
Page 29 and 30: Alternatives to Least-Squares Instr
Page 35 and 36: Alternatives to Least-Squares Maxim
Page 37 and 38: Alternatives to Least-Squares Maxim
Page 39 and 40: Practice Identification In Practice

EECE 574 - Adaptive Control - Basics of System Identification

Create successful ePaper yourself

Delete template?

Save as template?