Identification of combined physical and empirical models using nonlinear A priori knowledge

Control Engineering Practice

Volumn 3, Issue 3, 1995, Pages 375-382

  Kemna, A H ^a   Mellichamp, D A ^a  

^a UNIVERSITY OF CALIFORNIA   (United States)

Author keywords

a priori knowledge; canonical variate analysis; Identification; physical empirical models

Indexed keywords

DATA PROCESSING; MATHEMATICAL MODELS; NONLINEAR SYSTEMS; RELIABILITY; ROBUSTNESS (CONTROL SYSTEMS);

A PRIORI KNOWLEDGE; CANONICAL VARIATE; DATA EXTRACTION; PROCESS DYNAMICS;

IDENTIFICATION (CONTROL SYSTEMS);

EID: 0029267716     PISSN: 09670661     EISSN: None     Source Type: Journal    
DOI: 10.1016/0967-0661(95)00010-R     Document Type: Article

References (17)

1. Canonical Correlation Analysis of Time Series and the Use of an Information Criterion
2. Discrete-Time Adaptive Control Utilizing Prior Information
3. Parameter Identification Using Prior Information
4. Self-Tuning Control with A Priori Plant Knowledge
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6. Identification of Combined Physical/Empirical Models with Application to an Industrial Process
7. Dynamic Models of Recovery Boilers from Input/Output Data
8. Identification of Combined Physical and Empirical Models
9. Canonical Variate Analysis in Identification, Filtering, and Adaptive Control
10. On-Line Adaptive Control of Unstable Aircraft Wing Flutter
11. Identification of Chemical Processes Using Canonical Variate Analysis
12. Locally Robust Identification of Linear Systems Containing Unknown Gain Elements with Application to Adapted IIR Lattice Models
13. Adaptive Stability Augmentation