- Title
- Robust identification of continuous-time systems from sampled data
- Creator
- Yuz, Juan I.; Goodwin, Graham C.
- Relation
- Identification of Continuous-Time Models from Sampled Data p. 67-89
- Relation
- Advances in Industrial Control
- Publisher Link
- http://dx.doi.org/10.1007/978-1-84800-161-9
- Publisher
- Springer
- Resource Type
- book chapter
- Date
- 2008
- Description
- In this chapter we have explored the robustness issues that arise in the identification of continuous-time systems from sampled data. A key observation is that the fidelity of the models at high frequencies generally plays an important role in obtaining models suitable for continuous-time system identification. The problems discussed above have been illustrated for both, deterministic and stochastic systems. Special attention was given to the identification of continuous-time autoregressive stochastic models from sampled data. We have argued that traditional approaches to this problem are inherently sensitive to high-frequency modelling errors. We have also argued that these difficulties can be mitigated by using the proposed FDML with restricted bandwidth.
- Subject
- continuous-time systems; high-frequency; FDML; sampled data; robust
- Identifier
- uon:6613
- Identifier
- http://hdl.handle.net/1959.13/804442
- Identifier
- ISBN:9781848001602
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