Experiment design for MPC relevant identification

Proceedings of the American Control Conference

Volumn 4, Issue , 2002, Pages 2713-2718

  Gopaluni, Ratna Bhushan ^a   Patwardhan, Rohit S ^a   Shah, Sirish L ^a  

^a UNIVERSITY OF ALBERTA   (Canada)

Author keywords

[No Author keywords available]

Indexed keywords

COMPUTER SIMULATION; IDENTIFICATION (CONTROL SYSTEMS); MATHEMATICAL MODELS; MAXIMUM LIKELIHOOD ESTIMATION; OPTIMAL CONTROL SYSTEMS;

MODEL PREDICTIVE CONTROLLERS; OPTIMAL WEIGHTING; PREDICTION ERRORS;

PREDICTIVE CONTROL SYSTEMS;

EID: 0036061302     PISSN: 07431619     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/acc.2002.1025197     Document Type: Conference Paper

References (8)

1. Some results on optimal experiment design
2. Optimal experiment design for prediction error identification in view of feedback design
3. MPC relevant identification - Tuning the noise model
4. For model-based control design, closed loop identification gives better performance
5. The role of data prefiltering for integrated identification and model predictive control
6. Modelling and implicit modelling for predictive control
7. A control-relevant identification strategy for gpc